Modeling municipal solid waste collection: A generalized vehicle routing model with multiple transfer stations, gather sites and inhomogeneous vehicles in time windows

Optimizing the greenhouse gas emissions of waste transfer and transport: An integration of life cycle assessment and vehicle routing problem

This study presents a comprehensive analysis of greenhouse gas (GHG) emissions associated with waste transfer and transport, incorporating derived leachate treatment-a factor often overlooked in existing research. Employing an integration model of life cycle assessment and a vehicle routing problem (VRP) methods, we evaluated the GHG reduction potential of waste transfer and transport system. Two Chinese counties with different topographies and demographics were selected, yielding 80 scenarios that factored in waste source separation as well as vehicle capacity, energy sources, and routes. The functional unit (FU) is transferring and transporting 1 tonne waste and treating derived leachate. The GHG emissions varied from 12 to 39 kg CO2 equivalent per FU. Waste source separation emerged as the most impactful mitigation strategy, not only for the studied system but for an integrated waste management system. Followings are the use of larger capacity vehicles and electrification of the vehicles. These insights are instrumental for policymakers and stakeholders in optimizing waste management systems to reduce GHG emissions.

Data Science Applications in Circular Economy: Trends, Status, and Future

The circular economy (CE) aims to decouple the growth of the economy from the consumption of finite resources through strategies, such as eliminating waste, circulating materials in use, and regenerating natural systems. Due to the rapid development of data science (DS), promising progress has been made in the transition toward CE in the past decade. DS offers various methods to achieve accurate predictions, accelerate product sustainable design, prolong asset life, optimize the infrastructure needed to circulate materials, and provide evidence-based insights. Despite the exciting scientific advances in this field, there still lacks a comprehensive review on this topic to summarize past achievements, synthesize knowledge gained, and navigate future research directions. In this paper, we try to summarize how DS accelerated the transition to CE. We conducted a critical review of where and how DS has helped the CE transition with a focus on four areas including (1) characterizing socioeconomic metabolism, (2) reducing unnecessary waste generation by enhancing material efficiency and optimizing product design, (3) extending product lifetime through repair, and (4) facilitating waste reuse and recycling. We also introduced the limitations and challenges in the current applications and discussed opportunities to provide a clear roadmap for future research in this field.

Research on transportation management model of COVID-19 medical waste: a case study in Beijing, China

During the COVID-19 pandemic, disposable masks, protective clothing, gloves, and nasopharyngeal swabs collected by nucleic acid testing formed a large amount of medical waste. Medical waste has strict temporary storage time requirements in hospitals, which need to be transported to medical waste disposal plants within the specified time. However, as most of disposal plants are far away from downtown, they also need to be responsible for the transportation and disposal of medical waste in many hospitals, and put forward higher requirement for transportation routes. Rapid and safe disposal of all types of medical waste generated by COVID-19 is crucial to the prevention and control of the epidemic. This paper designs the transportation route optimization model using Anylogic simulation software based on the regional distribution of 118 tertiary hospitals and 2 large medical waste disposal plants in Beijing, China. At the same time, transportation routes of 118 tertiary hospitals in the morning peak, evening peak, all-day, and ordinary periods were simulated based on the Beijing traffic index in 2017. On this basis, through the analysis of the simulation data, the selection of medical waste transport routes for 118 tertiary hospitals in the morning peak, evening peak, all day, and ordinary periods is further clarified, so as to ensure that medical waste can be transported to the medical waste disposal plant in the shortest time. The shortest path and fastest speed transport mode, medical waste transport data set, and the selection of transport mode of 118 tertiary hospitals formed by this research provide certain reference experience for the rapid and safe transport of medical waste during the epidemic period, and also provides corresponding data support for medical waste transportation management in the post-epidemic era and medical waste transportation decision-making when facing major public health problems.

Government intervention in municipal waste collection with a sustainable approach: a robust bi-level problem

Conservation of the environment has taken a prime position among areas of concern for managers and practitioners worldwide. This study aims to provide a bi-level mathematical model for municipal waste collection considering the sustainability approach. The mathematical model with conflicting objects was proposed at the upper level of the model of maximizing government revenue from waste recycling and at the lower level of minimizing waste collection and recycling costs, which had stochastic parameters and was scenario based. A case study was conducted in the Saveh processing site (Iran). Due to the complexity of the bi-level model, the KKT approach was adopted to unify the model. Finally, the relevant calculations were performed based on actual information. The results of the problem in the case study showed the efficiency of the proposed method. Several computational analyses randomly generated different waste recycling rates and obtained significant management results.

Application of MCAT to provide multi-objective optimization model for municipal waste management system

Choosing an appropriate municipal waste management method is a very complicated environmental problem in cities. This research introduces an optimization model for waste management in the southwest region of Tehran province. It was developed by a metaheuristic algorithm that was used to minimize the economic and environmental costs. Incineration, composting, recycling and landfilling waste management methods were considered. Three scenarios were developed to determine the optimum allocation of waste to each method such to fulfill the objective of overall minimum of environmental burdens and costs. A multi-objective scenario selection model was implemented by the compromise programming method in MCAT software. Considering the budget limitation and available facilities on site, optimum allocations to recycling, composting, incineration and landfilling methods were obtained as 115,486, 132,094, 71,905 and 45,516 tons/year, respectively. The results of this study indicated that the metaheuristic algorithm in MCAT software was an efficient tool in decision making about waste management systems and thus, it was suggested to municipality managers and regional planning authorities.

Medical waste management during coronavirus disease 2019 (COVID-19) outbreak: A mathematical programming model

Municipal solid waste (MSW) directly impacts community health and environmental degradation; therefore, the management of MSW is crucial. Medical waste is a specific type of MSW which is generally divided into two categories: infectious and non-infectious. Wastes generated by coronavirus disease 2019 (COVID-19) are classified among infectious medical wastes; moreover, these wastes are hazardous because they threaten the environment and living organisms if they are not appropriately managed. This paper develops a bi-objective mixed-integer linear programming model for medical waste management during the COVID-19 outbreak. The proposed model minimizes the total costs and risks, simultaneously, of the population's exposure to pollution. This paper considers some realistic assumptions for the first time, including location-routing problem, time window-based green vehicle routing problem, vehicles scheduling, vehicles failure, split delivery, population risk, and load-dependent fuel consumption to manage both infectious and non-infectious medical waste. We apply a fuzzy goal programming approach for solving the proposed bi-objective model, and the efficiency of the proposed model and solution approach is assessed using data related to 13 nodes of medical waste production in a location west of Tehran.

Redesigning the Municipal Solid Waste Supply Chain Considering the Classified Collection and Disposal: A Case Study of Incinerable Waste in Beijing

The output of municipal solid waste is growing rapidly, which has brought tremendous pressure to urban development. The supply chain of municipal solid waste (MSW) in China mainly contains three processes: collection, transportation, and disposal. The waste is sorted at the collection and disposed of according to the classification. However, it is mixed at the transportation stage. Mixed transportation remixes the separately collected waste, which seriously affects the disposal effect. The supply chain of MSW urgently needs to be redesigned to improve the MSW disposal effect. First of all, on the ground of the waste treatment situation, we redesigned the supply chain of MSW in China. Secondly, combined with the redesign of the MSW supply chain, this paper established the function allocation model for collection stations, making a collection station only gather one type of waste, and built the transportation path planning model for vehicles, reducing the impact of waste storage on residents. Finally, based on the data of Xuanwu District in Beijing, the supply chain redesigning practical example of incinerable waste was given. The supply chain redesigning model in this paper not only makes full use of the existing infrastructure but also improves the disposal effect of waste. The supply chain redesigning model has practical application value.

Multi-Objective Optimization for Healthcare Waste Management Network Design with Sustainability Perspective

Healthcare Waste Management (HWM) is considered as one of the important urban decision-making problems due to its potential environmental, economic, and social risks and damages. The network of the HWM system involves important decisions such as facility locating, inventory management, and transportation management. Moreover, with growing concerns towards sustainable development objectives, HWM systems should address its environmental and social aspects as well as its economic and technical characteristics. In this regard, this paper formulates a novel multi-objective optimization model to empower companies in making optimized decisions considering the economic, environmental, and social aspects. Within the proposed model, the first objective function aims to minimize the transportation costs, processing costs, and establishment costs. The second objective function aims to minimize environmental risks and emissions related to the transportation of waste between facilities. The third objective function aims to maximize job creation opportunities. Formulating these three functions, an Improved Multi-Choice Goal Programing (IMCGP) approach is proposed to solve the multi-objective optimization model, which is then compared with the Goal Attainment Method (GAM). Finally, to show the applicability and feasibility of the proposed model, an illustrative example of healthcare waste management is analyzed, and the results are discussed.

A sustainable medical waste collection and transportation model for pandemics

We are currently experiencing a critical period for the prevention and control of the COVID-19 pandemic. COVID-19 related waste is a threat to global public environmental health. Medical waste management during this pandemic is one of the major issues facing public service organizations such as municipalities, which is of great importance in terms of logistics, environment and social aspects. The discussion of logistics operations is related to the collection, transportation and disposal of waste, which imposes high expenses. Many methods have been applied to develop and improve waste management policies in the literature. Apart from these studies, very few researchers have improved vehicle operations in waste management considering environmental aspects and the possibility of outsourcing. In this paper, by examining the gaps in the field, we try to explain and formulate the sustainable medical waste management problem for pandemics. Finally, by designing several practical examples with different scales, we solve the problem using CPLEX solver, compare different conditions and discuss the practical implications using the sensitivity analysis of demand parameter.

Municipal waste management and electrical energy generation from solid waste: a mathematical programming approach

Purpose

Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. The purpose of this study is to design a new model for municipal waste collection vehicle routing problems with time windows and energy generating from waste. To this purpose, a bi-objective model is presented with the objectives of increasing the income of waste recycles and energy generation from waste and reducing emissions from environmental pollutants.

Design/methodology/approach

A bi-objective model is presented with the objectives of increasing income of recycles trade and energy generation and reducing emissions from environmental pollutants. Concerning the complexity of the model and its inability to solve large-scale problems, non-dominated sorting genetic algorithms and multi-objective particle swarm optimization algorithms are applied.

Findings

In this research, an integrated approach to urban waste collection modeling that coordinates the various activities of waste management in the city of Kermanshah and energy generation from waste are provided. Besides, this study calculates the criteria that show the environmental effects of municipal waste. The proposed model helps to collect municipal wastes in the shortest possible time in addition to reducing the total cost, revenues from the sale of recycled materials and energy production.

Originality/value

The proposed model boosts the current understanding of the waste management and energy generation of waste. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

A novel cooperative model in the collection of infectious waste in COVID-19 pandemic

Purpose

Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors.

Design/methodology/approach

Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time.

Findings

The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model.

Originality/value

The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

Municipal solid waste transfer station planning through vehicle routing problem-based scenario analysis

Collection, transfer and transport of municipal solid waste (MSW) is one of the most challenging tasks of local municipalities and occupies a significant portion of the municipal expenses. Appropriately planned transfer stations (TSs) can increase system performance and reduce costs. Therefore, this study aims to develop a spatial modelling approach for investigating the optimum siting and economic impacts of MSW TSs. A geographic information system-based land suitability analysis was conducted to identify potential TS sites followed by a scenario analysis to determine optimum TS sites and waste collection routes for various collection vehicle capacities through vehicle routing problem modelling. The approach was implemented in the southeastern region of İzmir where a new landfill is to be built to serve three district municipalities. The addition of a TS in the study area reduced the collection time and number of shifts by 9%. Similarly, collection with large vehicles decreased the collection time and number of shifts by 25% and 17%, respectively. However, the unit cost of the system increased from 17.52 to 18.60 US$ metric tonnes^-1 waste with the TS addition because of the additional costs of the TS. The results indicated that TS addition is not economically feasible in the study area because of the small collection vehicle fleet (eight collection vehicles), proximity of landfill to areas with high waste density and district level collection. On the other hand, TS addition resulted in lower fuel consumption which may help reduce fuel-induced air pollution.

Bioconversion of municipal solid waste into bio-based products: A review on valorisation and sustainable approach for circular bioeconomy

Municipal solid waste management is one of the major issues throughout the world. Inappropriate management of municipal solid waste (MSW) can pose a major hazard. Anaerobic processing of MSW followed by methane and biogas generation is one of the numerous sustainable energy source options. Compared with other technologies applicable for the treatment of MSW, factors like economic aspects, energy savings, and ecological advantages make anaerobic processing an attractive choice. This review discusses the framework for evaluating conversion of municipal solid waste to energy and waste derived bioeconomy in order to address the sustainable development goals. Further, this review will provide an innovative work foundation to improve the accuracy of structuring, quality control, and pre-treatment for the ideal treatment of different segments of MSW to achieve a sustainable circular bioeconomy. The increasing advancements in three essential conversion pathways, in particular the thermochemical, biochemical, and physiochemical conversion methods, are assessed. Generation of wastes should be limited and resource utilization must be minimised to make total progress in a circular bioeconomy.

Network design of a household waste collection system: A case study of the commune of Renca in Santiago, Chile

This study proposes a design of a household waste collection system based on a two-stage procedure. First, the bin location-allocation problem is solved by selecting collection sites from a set of potential sites, and determining the type and number of bins at each selected collection site. Second, bin-to-bin waste collection routes are obtained for a fleet of homogeneous vehicles that are restricted by either work shift duration or vehicle capacity. Mixed integer linear programming (MILP) models are proposed for both stages, considering the particular characteristics of the problem. The models are applied to a real-world instance in the commune of Renca in Santiago, Chile. The results of first stage indicate an important preference for small bins since they have a lower unitary cost. Due to the large size of the real instance, a Large Neighborhood Search (LNS) heuristic is used in the second stage to find good feasible vehicle routing solutions in a reasonable period of time. The results for the routing phase suggest a larger number of routes in the morning work shift since these routes have shorter distances. The LNS heuristic presents a satisfactory behavior when compared to the MILP model with small instances. The proposed bin-to-bin household waste collection vehicle routing presents a more efficient solution than the existing door-to-door waste collection in the commune of Renca with respect to the total daily traveled distance and the average work shift duration. Finally, a sensitivity analysis is presented and discussed for both models.

A sustainable municipal solid waste system design considering public awareness and education: A case study

The municipal solid waste management (MSWM) system design considered here is effective in reducing supply chain costs and environmental risks. One of the practical approaches that governments use to encourage MSWM practices is educating households with regard to reducing waste generation and increasing recycling and composting rates. This research aims to utilize a new multi-objective stochastic optimization model to design a MSWM system, taking public awareness and educating the public into consideration. Further, the efficiency induced by educating the public is also taken into account using its corresponding factors in the model. In this article, two types of truck for collecting the mixed and separated waste are appraised. Due to the unpredictability of some of the parameters of the MSWM models, allowances are made for uncertainty. The proposed model is applied to a real case in Tehran, Iran. To show the impact of educating households, the model is compared with a similar model that does not take educating the public into account. The results show a reduction of 40% in the total cost and an increment of 17% in the social impact as opposed to the model that does not take educating the public into consideration. This acknowledges that educating the public will improve the results obtained.

A mixed integer linear programming model for long-term planning of municipal solid waste management systems: Against restricted mass balances

Long-term planning of municipal solid waste management systems is a complex decision making problem which includes a large number of decision layers. Since all different waste treatment and disposal processes will show different responses to each municipal solid waste component, it is necessary to separately evaluate all waste components for all processes. This obligation creates an obstacle in the programming of mass balances for long-term planning of municipal solid waste management systems. The development of an ideal mixed integer linear programming model that can simultaneously respond to all essential decision layers including waste collection, process selection, waste allocation, transportation, location selection, and capacity assessment has not been made possible yet due to this important modeling obstacle. According to the current knowledge of the literature, all mixed integer linear programming studies aiming to address this obstacle so far have had to restrict many different possibilities in their mass balances. In this study, a novel mixed integer linear programming model was formulated. ALOMWASTE, the new model structure developed in this study, was built to take into consideration different process, capacity, and location possibilities that may occur in complex waste management processes at the same time. The results obtained from a case study showed the feasibility of new mixed integer linear programming model obtained in this study for the simultaneous solution of all essential decision layers in an unrestricted mass balance. The model is also able to provide significant convenience for the multi-objective optimization of financial-environmental-social costs and the solution of some uncertainty problems of decision-making tools such as life cycle assessment.

Municipal solid waste management considering NGO’s role in consumer environmental awareness and government regulations for air pollution

Purpose

The purpose of this study is twofold: first, to examine the role of non-governmental organizations (NGOs) in increasing customer environmental awareness (CEA) to decrease the municipal solid waste (MSW), and secondly, to examine the effect of government policies in the amount of air pollution caused by transfer stations (TSs).

Design/methodology/approach

This study proposes a mixed-integer nonlinear programming model. For solving this multi-objective problem, the authors use epsilon constraint method, which presented eight Pareto solutions. For selecting the best solution, the analytic hierarchy process approach is used. The presented model is applied on a real case study, and the results are discussed and sensitivity analysis is implemented on the parameters of the concern.

Findings

This study confirms the assumption that by allocating budget to NGOs for increasing CEA, the produced waste will be decreased.

Research limitations/implications

In the present study, the authors only investigate air pollution caused by TS. Future studies can investigate other types of pollution. Furthermore, uncertainty in the amount of produced waste can be variable making the problem closer to the real environment. In this case, robust optimization may have better results.

Practical implications

Based on the results of sensitivity analysis, some implications obtain that can highlight by managers in the decision-making process. The operational costs of TS have a critical aspect in founding TS, so using new technology and high-tech machines for operational processes of TSs, can result in decreasing the running cost of TSs. Also, the determination of TS capacity is a remarkable issue in optimization, which should be paid special attention to this for the design of TSs in the planning phase of the system. Moreover, collaborating with NGOs has a good effect on increasing CEA that results in a decrease of MSW.

Originality/value

The role of NGOs and government simultaneity has been considered in a green supply chain. Moreover, the authors considered TS between source and disposal that reduce the time of transferring waste. Therefore, this study can be beneficial for the MSW management system, which faces the problems in the lack of capacity and transportation problems and environmental issues by proposing solutions in three studies including economic, environmental and social aspects.

A hybrid augmented ant colony optimization for the multi-trip capacitated arc routing problem under fuzzy demands for urban solid waste management

Nowadays, urban solid waste management is one of the most crucial activities in municipalities and their affiliated organizations. It includes the processes of collection, transportation and disposal. These major operations require a large amount of resources and investments, which will always be subject to limitations. In this paper, a chance-constrained programming model based on fuzzy credibility theory is proposed for the multi-trip capacitated arc routing problem to cope with the uncertain nature of waste amount generated in urban areas with the aim of total cost minimization. To deal with the complexity of the problem and solve it efficiently, a hybrid augmented ant colony optimization algorithm is developed based on an improved max-min ant system with an innovative probability function and a simulated annealing algorithm. The performance of hybrid augmented ant colony optimization is enhanced by using the Taguchi parameter design method to adjust the parameters' values optimally. The overall efficiency of the algorithm is evaluated against other similar algorithms using well-known benchmarks. Finally, the applicability of the suggested methodology is tested on a real case study with a sensitivity analysis to evolve the managerial insights and decision aids.

Interactions of residential waste composition and collection truck compartment design on GIS route optimization

Waste collection is an important functional element in a modern waste management system; and may account for up to half of the total expenditure on waste management in industrialized nations. Most optimization of waste collection studies include truck route distance and fuel consumption considerations without explicitly considering the inter-relationships of the model parameters. This study however delineates the complex inter-relationships of waste composition, collection frequency, collection type, and truck compartment configurations in a small waste collection zone in Austin, Texas. A total of 48 different scenarios are modelled and investigated. Truck travel distances are found sensitive to collection frequency, truck capacity, volume ratio of truck compartment, and waste density. The results showed that the increase in waste density and waste collection frequency helped to save up to 18.2% in travel distances and 41.9% in travel time. Waste composition is significant in travel distance, regardless of truck design. Increasing truck capacity by 25% helped to save 4.1-24.4% of truck travel distances. Optimal volume ratio of truck compartments was 50:50 (50% volume for garbage and 50% volume for recyclables); a finding that is different than what is currently reported in the literature; pointing to the site-specific nature of studies of this type. The use of dual compartment trucks helps to reduce travel distances by up to 23.0% and travel time by up to 14.3%. It appears that the minimization of operation time within the collection area is key to an efficient system.

Assessment of municipal solid waste selective collection scenarios with geographic information systems in Bolivia

The analysis of municipal solid waste (MSW) selective collection (SC) scenarios is compulsory for planning future policies and actions towards circular economy. The use of geographic information system (GIS) is appropriated for obtaining reliable data about SC yields and management costs. However, in low-middle income countries, advanced assessments are difficult to introduce due to the lack of technical knowledge, financial support and the presence of the informal recycling sector. This research aims to assess the main potentialities of the introduction of SC systems in a Bolivian developing city taking into account the informal SC system in place. The study was conducted with QGIS3.8 software in order to evaluate the main advantages of the implementation of formal and informal recycling chains. Results reported that, comparing the implementation of formal SC of MSW with the scenario that considered the inclusion of the informal recycling, the activity of waste pickers allows reducing the expenses of about 10%, increasing the recycling rate of about 3.5%, and reducing the distances traveled with compactor trucks of about 7%. It means that, the annual path traveled by the collection trucks for gathering about 16,000ty^-1, is reduced by 2734kmy^-1, reducing the waste disposed to landfill of about 543.6ty^-1 and the expenses of about €59,000 per year. The presentation of these results to policy-makers can support decision-making boosting the implementation of recycling activities including waste pickers. The study provided a contribution to the scientific literature assessing the main challenges and opportunities for implementing the circular economy in developing regions.

Collection of Solid Waste in Municipal Areas: Urban Logistics

A sustainable process satisfies the current needs without compromising the ability of future generations to satisfy their own needs; that is, it must have a triple impact (sustainability): social, economic, and environmental. In México, there are several services that the government must provide to society for its proper development, for example, the collection of solid waste. Urban logistics include all the processes and operations that provide a service to the community, such as water, safety, health, waste collection, etc., providing the service with the lowest possible cost (economic, social, and environmental) that contributes to the sustainability of the city. Due to the accelerated growth of the world population, several environmental problems have arisen, among them, the generation of solid waste in important quantities; their proper management is relevant for adequate development of the population. The collection of solid waste in municipal areas aims to grant green spaces and recreation areas for the citizens. Although an outstanding effort has been made by the government to provide an adequate service, there are still gaps in the application of correct tools that guarantee efficiency in operations and continuity in services. This article presents a proposal to improve the planning of the design of territories for the cleaning, weeding, and collection of solid waste in municipal areas, using two MILP (Mixed Integer Linear Programming) models. The main contribution of the adaptation of this model is the application to the weeding and waste collection service municipality of the Monterrey Metropolitan Area, which considers important factors among which are the amount of waste, frequency, and service coverage.

Regional Differences in Municipal Solid Waste Collection Quantities in China

The rapid growth in urban population has led to a dramatic increase in municipal solid waste (MSW) generation, with ramifications more pronounced in developing countries. The regional Chinese governments have made great efforts to reduce MSW generation and collection quantities. However, the results of these efforts vary across cities. The purpose of this paper is to analyze the regional differences in MSW collection quantities. A two-level hierarchical linear model (HLM) was used to examine the variations in MSW collection quantities among 287 prefecture-level cites in China over the period from 2008 to 2017. The analysis reveals a strong negative correlation between the regional economic development level and the growth trend of MSW collection quantities. The empirical findings indicate that the level of economic development and waste collection measures are critical determinants of MSW collection quantities.

Multi-stage optimization approach for sustainable municipal solid waste collection systems in urban areas of Asia's newly industrialized countries

A multi-stage optimization approach for sustainable collection system design for urban municipal solid waste is developed for megacities in Asia's newly industrialized countries. The approach combines four methods-analysis of waste and area characteristics, data acquisition and evaluation by GIS, mathematical projection of existing and future collection systems, and identification of most suitable alternatives through comparative multi-criteria decision analysis (MCDA). The approach is applied in Bangalore, India with 1.66 million inhabitants and 46.7-km² area of investigation, and stratified based on population density. Two possible collection mechanisms (door-to-door (D2D) and community bin (CB)) are analyzed with a varied combination of collection coverage and waste segregation level. The study results confirm that both operational and investment expenses of the collection system decrease with an increasing rate of CB collection. Moreover, overall CO₂ emissions of waste collection from the entire area of investigation decrease from 5.2 to 3.1 tons per day if the present 100% D2D collection is replaced with 100% CB collection system. Also, the increase of segregation at source contributes to the reduction of operational expenses and CO₂ emissions; for example, a 20% increase of segregation level for D2D collection system leads to a 6% reduction of CO₂ emissions. Considering all decision parameters through MCDA, a collection system comprising only CB with one separate compartment for wet waste and another combined compartment for dry and mixed waste is determined to be the most favorable approach.

Network Design for Municipal Solid Waste Collection: A Case Study of the Nanjing Jiangbei New Area

Garbage collection is an important part of municipal engineering. An effective service network design can help to reduce the municipal operation cost and improve its service level. In this paper, we propose an optimization model for the network design of municipal solid waste (MSW) collection in the Nanjing Jiangbei new area. The problem was formulated as a mixed integer nonlinear programming (MINLP) model with an emphasis on minimizing the annual operation cost. The model simultaneously decides on the optimal number of refuse transfer stations (RTSs), determines the relative size and location for each RTS, allocates each community to a specific RTS, and finally identifies the annual operation cost and service level for the optimal scenario as well as other scenarios. A custom solution procedure which hybrids an enumeration rule and a genetic algorithm was designed to solve the proposed model. A sensitivity analysis was also conducted to illustrate the impact of changes in parameters on the optimality of the proposed model. Test results revealed that our model could provide tangible policy recommendations for managing the MSW collection.

Life-cycle cost as basis to optimize waste collection in space and time: A methodology for obtaining a detailed cost breakdown structure

Extensive research has been carried out on waste collection costs mainly to differentiate costs of distinct waste streams and spatial optimization of waste collection services (e.g. routes, number, and location of waste facilities). However, waste collection managers also face the challenge of optimizing assets in time, for instance deciding when to replace and how to maintain, or which technological solution to adopt. These issues require a more detailed knowledge about the waste collection services' cost breakdown structure. The present research adjusts the methodology for buildings' life-cycle cost (LCC) analysis, detailed in the ISO 15686-5:2008, to the waste collection assets. The proposed methodology is then applied to the waste collection assets owned and operated by a real municipality in Portugal (Cascais Ambiente - EMAC). The goal is to highlight the potential of the LCC tool in providing a baseline for time optimization of the waste collection service and assets, namely assisting on decisions regarding equipment operation and replacement.

SGA: spatial GIS-based genetic algorithm for route optimization of municipal solid waste collection

Designing optimization models and meta-heuristic algorithms for minimization of traveling routes of vehicles in solid waste collection has been gaining interest in environmental modeling. The computer models and methods are useful to bring out specific strategies for prevention and precaution of possible disasters that could be foreseen worldwide. This paper proposes a new Spatial Geographic Information System (GIS)-based Genetic Algorithm for optimizing the route of solid waste collection. The proposed algorithm, called SGA, uses a modified version of the original Dijkstra algorithm in GIS to generate optimal solutions for vehicles. Then, a pool of solutions, which are optimal routes of all vehicles, is encoded in Genetic Algorithm. It is iteratively evolved to a better one and finally to the optimal solution. Experiments on the case study at Sfax city in Tunisia are performed to validate the performance of the proposal. It has been shown that the proposed method has better performance than the practical route and the original Dijkstra method.

Parameter interrelationships in a dual phase GIS-based municipal solid waste collection model

Geographic information systems are a valuable tool for waste collection and optimization, but they have been underutilized in helping to understand the complex interrelationships that exist within a dual phase solid waste collection system. A GIS-based dual phase model integrating the handcart pre-collection phase and truck collection phase for a study area located in Hai Phong, Vietnam was proposed, and a resulting total system cost was estimated. Temporary collection points were first identified using both the maximize coverage and minimize facility location-allocation tools from a list of candidate temporary collection points and constraints. Two vehicle routing problems were then separately modeled for handcart and truck routes. A total of 30 scenarios were considered in order to investigate the interrelationships between the model parameters, with respect to the total operation costs and maintenance system costs. The scenario with 11 temporary collection points and a maximum handcart collection distance of 500 m gave the lowest overall cost in the study area. The results suggest a single temporary collection point in the study is able to serve about 2,590 people in an area of 0.11 km². Compared to the status quo condition, a 13.76% reduction in truck travel distances is attainable using the proposed model. It is found that the number and distribution of temporary collection points greatly affected the cost effectiveness in both pre-collection and collection phases.

Household food waste collection: Building service networks through neighborhood expansion

In this paper we develop a residential food waste collection analysis and modeling framework that captures transportation costs faced by service providers in their initial stages of service provision. With this framework and model, we gain insights into network transportation costs and investigate possible service expansion scenarios faced by these organizations. We solve a vehicle routing problem (VRP) formulated for the residential neighborhood context using a heuristic approach developed. The scenarios considered follow a narrative where service providers start with an initial neighborhood or community and expands to incorporate other communities and their households. The results indicate that increasing household participation, decreases the travel time and cost per household, up to a critical threshold, beyond which we see marginal time and cost improvements. Additionally, the results indicate different outcomes in expansion scenarios depending on the household density of incorporated neighborhoods. As household participation and density increases, the travel time per household in the network decreases. However, at approximately 10-20 households per km², the decrease in travel time per household is marginal, suggesting a lowerbound household density threshold. Finally, we show in food waste collection, networks share common scaling effects with respect to travel time and costs, regardless of the number of nodes and links.

Solid Waste Management Solutions for a Rapidly Urbanizing Area in Thailand: Recommendations Based on Stakeholder Input

Municipal solid waste is a significant problem, particularly in developing countries that lack sufficient infrastructure and useable land mass to process it in an appropriate manner. Some developing nations are experiencing a combination of issues that prevent proper management of solid waste. This paper reviews the management of municipal solid waste in northeast Thailand, using the Tha Khon Yang Sub-district Municipality (TKYSM) in Maha Sarakham Province as a case study. The combination of rapid population and economic growth and its associated affluence has led to an increase in the use of consumer items and a concomitant increase in the production of municipal solid waste. In the TKYSM there is pressure on local government to establish a suitable waste management program to resolve the escalating waste crisis. The aim of this study is to provide viable solutions to waste management challenges in the TKYSM, and potentially to offer guidance to other similar localities also facing the same challenges. It is well established that successful changes to waste management require an understanding of local context and consideration of specific issues within a region. Therefore, extensive community consultation and engagement with local experts was undertaken to develop an understanding of the particular waste management challenges of the TKYSM. Research methods included observations, one-on-one interviews and focus groups with a range of different stakeholders. The outcomes of this research highlight a number of opportunities to improve local infrastructure and operational capacity around solid waste management. Waste management in rural and urban areas needs to be approached differently. Solutions include: development of appropriate policy and implementation plans (based around the recommendations of this paper); reduction of the volume of waste going to landfill by establishing a waste separation system; initiation of a collection service that supports waste separation at source; educating the citizens of the municipality; and the local government staff, and for the local government to seek external support from the local temples and expertise from the nearby university.

A robust periodic capacitated arc routing problem for urban waste collection considering drivers and crew's working time

In this paper, a novel mathematical model is developed for robust periodic capacitated arc routing problem (PCARP) considering multiple trips and drivers and crew's working time to study the uncertain nature of demand parameter. The objective function of the proposed model aims to minimize total traversed distance and total usage cost of vehicles over a planning period. To solve the problem, an improved hybrid simulated annealing algorithm (SA) is developed based on a heuristic algorithm and an efficient cooling equation. It has been proved that the performance of the proposed algorithm is acceptable in comparison with the exact solution method. Finally, the results have shown the effects of different uncertainty level of the demand parameter on the problem to be considered as a managerial overview in decision making process under uncertainty.

Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm

Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts.

An optimization model for collection, haul, transfer, treatment and disposal of infectious medical waste: Application to a Greek region

The objective of this work was to develop an optimization model to minimize the cost of a collection, haul, transfer, treatment and disposal system for infectious medical waste (IMW). The model calculates the optimum locations of the treatment facilities and transfer stations, their design capacities (t/d), the number and capacities of all waste collection, transport and transfer vehicles and their optimum transport path and the minimum IMW management system cost. Waste production nodes (hospitals, healthcare centers, peripheral health offices, private clinics and physicians in private practice) and their IMW production rates were specified and used as model inputs. The candidate locations of the treatment facilities, transfer stations and sanitary landfills were designated, using a GIS-based methodology. Specifically, Mapinfo software with exclusion criteria for non-appropriate areas was used for siting candidate locations for the construction of the treatment plant and calculating the distance and travel time of all possible vehicle routes. The objective function was a non-linear equation, which minimized the total collection, transport, treatment and disposal cost. Total cost comprised capital and operation costs for: (1) treatment plant, (2) waste transfer stations, (3) waste transport and transfer vehicles and (4) waste collection bins and hospital boxes. Binary variables were used to decide whether a treatment plant and/or a transfer station should be constructed and whether a collection route between two or more nodes should be followed. Microsoft excel software was used as installation platform of the optimization model. For the execution of the optimization routine, two completely different software were used and the results were compared, thus, resulting in higher reliability and validity of the results. The first software was Evolver, which is based on the use of genetic algorithms. The second one was Crystal Ball, which is based on Monte Carlo simulation. The model was applied to the Region of East Macedonia - Thrace in Greece. The optimum solution resulted in one treatment plant located in the sanitary landfill area of Chrysoupolis, required no transfer stations and had a total management cost of 38,800 €/month or 809 €/t. If a treatment plant is sited in the most eastern part of the Region, i.e., the industrial area of Alexandroupolis, the optimum solution would result in a transfer station of 23 m³, located near Kavala General Hospital, and a total cost of 39,800 €/month or 831 €/t. A sensitivity analysis was conducted and two alternative scenarios were optimized. In the first scenario, a 15% rise in fuel cost and in the second scenario a 25% rise in IMW production were considered. At the end, a cost calculation in €/t/km for every type of vehicle used for haul and transfer was conducted. Also, the cost of the whole system was itemized and calculated in €/t/km and €/t. The results showed that the higher percentage of the total cost was due to the construction of the treatment plant.

A multi-objective model for sustainable recycling of municipal solid waste

The efficient management of municipal solid waste is a major problem for large and populated cities. In many countries, the majority of municipal solid waste is landfilled or dumped owing to an inefficient waste management system. Therefore, an optimal and sustainable waste management strategy is needed. This study introduces a recycling and disposal network for sustainable utilisation of municipal solid waste. In order to optimise the network, we develop a multi-objective mixed integer linear programming model in which the economic, environmental and social dimensions of sustainability are concurrently balanced. The model is able to: select the best combination of waste treatment facilities; specify the type, location and capacity of waste treatment facilities; determine the allocation of waste to facilities; consider the transportation of waste and distribution of processed products; maximise the profit of the system; minimise the environmental footprint; maximise the social impacts of the system; and eventually generate an optimal and sustainable configuration for municipal solid waste management. The proposed methodology could be applied to any region around the world. Here, the city of Tehran, Iran, is presented as a real case study to show the applicability of the methodology.

Optimization of municipal solid waste transportation by integrating GIS analysis, equation-based, and agent-based model

The amount of municipal solid waste (MSW) has been increasing steadily over the last decade by reason of population rising and waste generation rate. In most of the urban areas, disposal sites are usually located outside of the urban areas due to the scarcity of land. There is no fixed route map for transportation. The current waste collection and transportation are already overloaded arising from the lack of facilities and insufficient resources. In this paper, a model for optimizing municipal solid waste collection will be proposed. Firstly, the optimized plan is developed in a static context, and then it is integrated into a dynamic context using multi-agent based modelling and simulation. A case study related to Hagiang City, Vietnam, is presented to show the efficiency of the proposed model. From the optimized results, it has been found that the cost of the MSW collection is reduced by 11.3%.

A mathematical model for municipal solid waste management - A case study in Hong Kong

With the booming economy and increasing population, the accumulation of waste has become an increasingly arduous issue and has aroused the attention from all sectors of society. Hong Kong which has a relative high daily per capita domestic waste generation rate in Asia has not yet established a comprehensive waste management system. This paper conducts a review of waste management approaches and models. Researchers highlight that mathematical models provide useful information for decision-makers to select appropriate choices and save cost. It is suggested to consider municipal solid waste management in a holistic view and improve the utilization of waste management infrastructures. A mathematical model which adopts integer linear programming and mixed integer programming has been developed for Hong Kong municipal solid waste management. A sensitivity analysis was carried out to simulate different scenarios which provide decision-makers important information for establishing Hong Kong waste management system.