Human risk assessment of Panchet Dam in India using TOPSIS and WASPAS Multi-Criteria Decision-Making (MCDM) methods

Fishery, growth, mortality, and stock assessment of endangered Tor putitora from Tehri dam reservoir, Uttarakhand, Himalayan foothills of India in relation to environmental variables

The current study determined Tor putitora (Hamilton, 1822) fishery, growth, mortality, and population characteristics using length-frequency data assembled monthly from the Tehri dam reservoir in Uttarakhand from January to December 2022. The estimation data was separated into 40-mm class intervals, and population parameters were investigated and computed using the FiSAT-II software tool. W = 0.0101 L2.996, where a = 0.0101 and b = 2.99, were determined as the length-weight relationships, and the growth performance index (ϕ) was computed to be 5.40. Tor putitora commercial catches in the Tehri dam reservoir were dominated by length groups of 360-399 and 320-359 mm. Different growth parameters were estimated using length-frequency data as L∞ = 987.00 mm, K = 0.26 yr-1, and t0 = -0.0003 years. Z, M, and F mortality coefficients were estimated to be 1.01, 0.27, and 0.73, respectively. At the end of the first, second, third, fourth, fifth, sixth, and seventh years, the fish measured 226, 400, 535, 638, 718, and 780, and 827, respectively. The estimated value of the exploitation rate (E) was 0.73 using the length-converted catch curve approach, which was determined to be somewhat higher than the optimum value (0.50). Tor putitora recruitment patterns from the Tehri dam reservoir reveal that the species only has one recruitment pattern every year, and that solely occurs from June to September. The current exploitation level (0.73) has already exceeded the maximum fishing pressure (Emax = 0.508), indicating that there is a decline in the catch at the current fishing pressure, and a further increase in fishing efforts may lead to a decline in the stock, which may be detrimental to the sustainable fishery of Tor putitora in the Tehri dam reservoir, Uttarakhand, India.

A comparison among optimization software to solve bi-objective sectorization problem

In this study, we compare the performance of optimization software to solve the bi-objective sectorization problem. The used solution method is based on an approach that has not been used before in the literature on sectorization, in which, the bi-objective model is transformed into single-objective ones, whose results are regarded as ideal points for the objective functions in the bi-objective model. Anti-ideal points are also searched similarly. Then, using the ideal and anti-ideal points, the bi-objective model is redefined as a single-objective one and solved. The difficulties of solving the models, which are basically non-linear, are discussed. Furthermore, the models are linearized, in which case how the number of variables and constraints changes is discussed. Mathematical models are implemented in Python's Pulp library, Lingo, IBM ILOG CPLEX Optimization Studio, and GAMS software, and the obtained results are presented. Furthermore, metaheuristics available in Python's Pymoo library are utilized to solve the models' single- and bi-objective versions. In the experimental results section, benchmarks of different sizes are derived for the problem, and the results are presented. It is observed that the solvers do not perform satisfactorily in solving models; of all of them, GAMS achieves the best results. The utilized metaheuristics from the Pymoo library gain feasible results in reasonable times. In the conclusion section, suggestions are given for solving similar problems. Furthermore, this article summarizes the managerial applications of the sectorization problems.

An integrated of fuzzy-WASPAS and E-FMEA methods for environmental risk assessment: a case study of petrochemical industry, Iran

Due to the scope and volume of activities, the petrochemical industry has a high potential for risk to humans and the environment. This study aimed to evaluate the environmental risks caused by the ammonia and urea production process. To screen the risks identified in the follow-up phase, the process hazard analysis (PHA) was used. The environmental aspects were also assessed using environmental failure mode and effects analysis (EFMEA). The most significant environmental aspect with a Risk Priority Number (RPN) of 100 was related to CO₂ emissions from the disposal tower. To rank the final aspects, the criteria "severity," "probability of occurrence," "probability of detection," and the "extent of contamination" were first weighed by the fuzzy Shannon entropy method. Then, each aspect was prioritized based on the mentioned criteria and using fuzzy Weighted Aggregated Sum Product Assessment (WASPAS). According to this technique, among the 24 environmental aspects, the highest score (with a value of 0.702) was given to CO₂ emissions from the disposal tower. Finally, suggestions were made to mitigate the risks.

Risk prioritization model driven by success factor in the light of multicriteria decision making

Some factors in the product development process can increase success. Evaluating the risks and success factors is necessary for a more successful product development process. Some inadequacies arise in classical risk assessment methods due to the subjective nature of likelihood and severity ratings. Different probability and impact values can give the same risk size. Due to these inadequacies, doubts about the accuracy of risk prioritization may arise. In this study, a new risk prioritization model is proposed to eliminate these doubts and to consider their contribution to the success of the process they affect while prioritizing the risks, with a detailed literature review and the support of the experts of the applied company, the risks affecting the product development process. The importance levels of risks and success factors were calculated using the analytical hierarchy process. With the proposed model, unlike the classical method, when calculating the risk size, the risk weight and the total score from the success factors are added to the likelihood and severity values of the risk. Thus, companies will obtain more detailed and objective results, considering success factors and risk importance levels, and use the resources they allocate for risk reduction activities more efficiently.

Prioritizing and Overcoming Barriers to e-Health Use among Elderly People: Implementation of the Analytical Hierarchical Process (AHP)

Rise in the aging population brings new challenges to modern societies. Old age is associated with several morbidities and usual issues related to health. Therefore, the provision of healthy and timely care has become the dire need to maintain their quality of life and wellbeing. The evolution of the e-health care system put pressure on societies to implement it successfully to ensure a safe and prompt provision of care services to the most vulnerable population successfully. Therefore, the provision and implementation of the e-health care system is a challenge for the health industry in terms of multi-objective decision-making. Multicriteria decision-making is a generalizable approach to making decisions with dependence and feedback and is known as an effective tool in decision-making processes, particularly in the healthcare sector. The present study aims to present an e-healthcare framework by identifying and prioritizing potential barriers towards the use of e-health by the elderly population. The analytical hierarchy process approach is adopted to calculate weights of identified potential barriers, respectively, and then rank them based on their degree of significance. The findings show that health and the ability-related barrier is ranked highest, followed by socio-environmental and attitudinal barriers. This research contributes to healthcare decision-making regarding e-health usage by implementing MCDA techniques. Our study will assist the public health practitioners and policymakers in drawing decisions on the best strategy to minimize the risks in using the e-healthcare system by the aging population, which significantly contributes to the smart healthcare system.

Prioritization of water erosion-prone sub-watersheds using three ensemble methods in Qareaghaj catchment, southern Iran

Water-induced erosion poses severe harm to the sustainable development of land and water resources that is essential for attaining agricultural sustainability in Qareaghaj catchment of Fars Province, Iran. This study evaluates the topo-hydrological, morphometric, climatic, and environmental characteristics of Qareaghaj catchment for prioritizing the sub-watersheds that are susceptible to erosion caused by water. We tested and compared a novel ensemble multi-criteria decision-making (MCDM) model, namely the weighted aggregated sum product assessment-analytical hierarchy process (WASPAS-AHP) with prevailing benchmark ensemble MCDM models including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR)-AHP and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-AHP for ranking sub-watersheds and determining the most significant parameter that influences water erosion (WE) in Qareaghaj catchment. The outcome of weights using pairwise comparison matrix (PCM) of AHP reveals that normalized difference vegetation index (NDVI), mean annual rainfall (MAR), slope degree (SD), and slope length and steepness factor (LS) governs the WE in Qareaghaj catchment. The prioritization rankings of sub-watersheds obtained using the VIKOR-AHP, TOPSIS-AHP, and WASPAS-AHP models demonstrate that SW31, SW63, and SW94 had the highest priority rank with a score of 0.047, 0.69, and 0.477, respectively. The comparison of rankings from the models using Spearman's correlation coefficient tests (SCCT) and Kendall's tau correlation coefficient tests (KTCCT) revealed that WASPAS-AHP had a higher correlation with TOPSIS-AHP and VIKOR-AHP ensemble models. The outcome of MCDM models was validated based on the erosion potential method (EPM), which displayed that the VIKOR-AHP model was better for mapping the erosion susceptibility than TOPSIS-AHP and WASPAS-AHP models. Thus, the erosion susceptibility mapping based on the VIKOR-AHP ensemble model can be considered for developing new strategies and land use policies in order to control WE in Qareaghaj catchment.

A comparative multi criteria decision analysis of football teams: evidence on FIFA world cup

Purpose

World Cup tournament is one of the most popular international organizations in football. The purpose of this paper is to investigate the overall performance of World Cup 2018 teams via multi-criteria decision-making (MCDM) approaches.

Design/methodology/approach

The presented approach adopts entropy integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum Product Assessment (WASPAS) approaches to weight the criteria and evaluate the performance of World Cup 2018 teams. Initially, the authors compute weight criteria via Shannon Entropy method. Then, the authors compute and compare the results of TOPSIS and WASPAS methods so as to evaluate the performance of World Cup 2018 teams.

Findings

According to TOPSIS and WASPAS results, Belgium has demonstrated better performance in comparison to other teams. As per to the empirical results, both methods have shown a significant harmony in terms of performance figures. There is also strong positive correlation between TOPSIS and WASPAS method results. This result confirms the stability of the analysis.

Originality/value

This paper contributes to sport performance management literature by using MCDM methods in FIFA World Cup 2018 teams. To the best of the authors’ knowledge, this is the first paper to measure performance of an international football organization via MCDM methods.

A Dispatching-Fuzzy AHP-TOPSIS Model for Scheduling Flexible Job-Shop Systems in Industry 4.0 Context

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key aspect to be addressed in this particular aim is the adoption of a multi-criteria approach incorporating the current dynamics of smart FJSS. Thus, this paper proposes an integrated and enhanced method of a dispatching algorithm based on fuzzy AHP (FAHP) and TOPSIS. Initially, the two first steps of the dispatching algorithm (identification of eligible operations and machine selection) were implemented. The FAHP and TOPSIS methods were then integrated to underpin the multi-criteria operation selection process. In particular, FAHP was used to calculate the criteria weights under uncertainty, and TOPSIS was later applied to rank the eligible operations. As the fourth step of dispatching the algorithm, the operation with the highest priority was scheduled together with its initial and final time. A case study from the smart apparel industry was employed to validate the effectiveness of the proposed approach. The results evidenced that our approach outperformed the current company’s scheduling method by a median lateness of 3.86 days while prioritizing high-throughput products for earlier delivery.

Dealing with Water Conflicts: A Comprehensive Review of MCDM Approaches to Manage Freshwater Ecosystem Services

This paper presents a comprehensive review of the application of Multiple-Criteria Decision-Making (MCDM) approaches exclusively to water-related freshwater ecosystem services. MCDM analysis has been useful in solving conflicts and it works well in this framework, given the serious conflicts historically associated with water use and the protection of freshwater ecosystems around the world. In this study, we present a review of 150 papers that proposed the use of MCDM-based methods for the social, economic, or ecological planning and management of water ecosystem services over the period 2000–2020. The analysis accounts for six elements: ecosystem service type, method, participation, biogeographical realm, waterbody type, and problem to solve. A Chi-square test was used to identify dependence between these elements. Studies involving the participation of stakeholder groups adopted an integrated approach to analysing sustainable water management, considering provisioning, regulating, and cultural services. However, such studies have been in decline since 2015, in favour of non-participatory studies that were strictly focused on ecological and provisioning issues. Although this reflects greater concern for the health of freshwater ecosystems, it is a long way removed from the essence of ecosystem services, which entails an integrated approach to the interrelationships between hydrology, landscapes, ecology, and humans.

Implementation of multi-criteria decision method for selection of suitable material for development of horizontal wind turbine blade for sustainable energy generation

The material selection process for producing a horizontal axis wind turbine blade for sustainable energy generation is a vital issue when using Nigeria as a case study. Due to the challenge faced with the low wind speed variations. However, this paper focuses on implementing MCDM for the material selection process for a suitable material for developing a horizontal wind turbine blade. This paper used a quantitative research approach using AHP and TOPSIS multi-criteria decision method. The study put into consideration the environmental conditions for the material selection process when designing the questionnaire. The authors extracted the data used for the selection process from the 130 research questionnaire distributed to materials engineers and renewable energy professionals. This research considered four alternatives that is, aluminum alloy, stainless steel, glass fiber, and mild steel to determine the best material for the wind turbine blade. Also, the model has four criteria and eight sub-criteria used for developing the pair-wise matrix and the performance score used for the ranking process of the alternatives. The result shows that a consistency index of 0.056 and a consistency ratio of 0.062 gotten via the AHP method is workable for material selection practice. 78%, 43%, 67%, and 25% are the performance scores for the four alternatives via the TOPSIS techniques. In conclusion, aluminum alloy is the best material, followed by glass fibre. Therefore, the decision-makers recommended aluminum alloy; hence, manufacturers should apply aluminum alloy to develop the wind turbine blade for sustainable energy generation.