Dry Port Terminal Location Selection by Applying the Hybrid Grey MCDM Model

Grey hybrid normalization with period based entropy weighting and relational analysis for cities rankings

Researchers have addressed uncertainty in multicriteria decision making from the perspective of the performance values of the alternatives, weighting of the evaluation criteria, and the evaluation methods. Still, they are yet to address the uncertainty caused by the normalization approach. In this paper, we show that different normalization methods, namely sum normalization, min-max normalization, vector normalization, and maximization normalization, can result in different rankings of the alternatives while the performance values and weights are unchanged. We applied the grey system theory to address the problem of uncertainty in this study from three aspects: alternative performance values measurement, criteria weighting, and decision matrix/table normalization within a period. The grey hybrid normalization method is proposed as the main contribution in this paper. Then, we present the rankings of 48 cities under uncertainty to decide the location of a branch office of a Chinese electric vehicle manufacturer as a practical example based on the grey entropy weighting method and grey relational analysis with positive and negative references (GRA-PNR) within the period from the year 2019 to 2021. The research results using this approach ranked New York City the best, with a stock market capitalization of economy validity as the top contributor in terms of weighting. Finally, we used simple additive weighting with grey value and the technique for order of preference by similarity to ideal solution with grey value methods to validate the study results.

Evaluation of container port sustainability using WASPAS technique using on type-2 neutrosophic fuzzy numbers

According to the common opinion in the literature, the sustainability of container ports is a tremendously complex topic owing to the maritime sector's excessively dynamic form and many highly complex, predictable and unpredictable uncertainties in this industry. The current paper proposes two powerful, practical, inspiring approaches to fill these gaps. It proposes a novel type-2 neutrosophic fuzzy numbers (T2NFNs) based Delphi method to determine the criteria logically and optimal and extends the WASPAS technique based on the T2NFNs for evaluating the alternatives. The current paper presents practical managerial implications that many stakeholders can consider, such as port authorities, ship owners, logistics service providers, governments, and local authorities, when making strategic and managerial decisions. In addition, the results of a comprehensive sensitivity analysis performed to test the robustness and applicability of the model approve the validity of the proposed T2NFN-based integrated approach.

Logistics Service Provider Evaluation and Selection: Hybrid SERVQUAL–FAHP–TOPSIS Model

Production and business enterprises are aiming to improve their logistics activities in order to increase competitiveness. Therefore, the criteria and decision support models for selecting logistics service providers are significant to businesses. Fuzzy theory has been applied to almost all industrial engineering fields, such as decision making, operations research, quality control, project scheduling and many more. In this research, the authors combined fuzzy theory and a Multicriteria Decision Making (MCDM) model for the evaluation and selection of potential third-party logistics (3PL) providers. The goal is to take the advantages of these approaches and allow for more accurate and balanced (symmetric) decision making through their integration. The main contribution of this study is that it develops a complete approach to assessing the quality of the logistics service industry. The combined method of the SERVQUAL and FAHP–TOPSIS models not only provides reasonable results, but it also allows decision makers to visualize the impact of different criteria on the final outcome. Furthermore, this integrated model can provide valuable insights and methods for other areas to define service quality.

Optimization of Cold Chain Logistics with Fuzzy MCDM Model

Vaccines are biological products containing a weakened, inactivated part of bacteria or viruses that are not harmful to the human body. Vaccine manufacturers and distributors should always store vaccines at the right temperature. To do this task, manufacturers and distributors need to manage cold supply chains to the required standards. Cold chain management helps manufacturers control and keep vaccines at the right temperature while ensuring quality and extending their expiration date. That will help businesses in the medical industry reduce economic losses, avoid waste, and bring more significant benefits to patients. The selection and evaluation process for logistics suppliers, especially those who deal with low-temperature storage, considers many factors to reduce the potential waste of products from poor storage strategies. The author introduces an integrated approach to solve such a fuzzy multiple criteria decision-making (MCDM) problem based on the Fuzzy Analytical Hierarchy Process (FAHP) model and an Interactive and Multi-criteria Decision-Making in Portuguese Model (TODIM) model methods under the fuzzy linguistic environment. In this work, the SF-AHP method derives criteria weights in the first stage, and then a TODIM method is presented to identify the ranking of logistics providers. Finally, the authors present a case study on the evaluation and selection of cold chain logistics suppliers to demonstrate the applicability of the proposed fuzzy MCDM model.

Solar Energy Deployment for the Sustainable Future of Vietnam: Hybrid SWOC-FAHP-WASPAS Analysis

In recent years, solar power has developed significantly in Vietnam, making an important contribution to ensuring energy conservation and decreasing greenhouse gas exposure. Recently, Vietnam has experienced impressive growth in the solar and wind energy sectors, showing the high potential of using renewable electricity in addressing energy needs. The target of this study was to construct a fuzzy multicriteria decision-making, model including strengths-weaknesses-opportunities-challenges (SWOC) analysis, the fuzzy analytic hierarchy process (F-AHP) model, and the weighted aggregates sum product assessment (WASPAS) model, to select the location of a solar power plant in south Vietnam. The proposed fuzzy multicriteria decision-making model (MCDM) model is the first solar power plant location selection in southern Vietnam that utilizes literature reviews and expert interviews. Moreover, this is the first study to provide a case study on evaluating locations during solar power plant location selection that utilizes a combination of the SWOC, FAHP, and WASPAS models. The findings of this study provide valuable knowledge for the assessment and selection of suitable locations for renewable energy projects, including both solar power energy projects and other renewable energy projects.

A Comparative Evaluation of Multi-Criteria Analysis Methods for Sustainable Transport

The article pertains to the utilization of the application potential of MCDM/MCDA (Multi-Criteria Decision Making/Multi-Criteria Decision Analysis) methods in decision-making problems in the field of transport in light of sustainable development. The article consists of a theoretical and an empirical part. As part of the literature studies, a review was carried out on the latest applications of MCDM/MCDA methods for decision-making problems in the field of transport. In the empirical part, a multi-criteria analysis of the placement selection for a strip of expressway located in north-eastern Poland was carried out. For this purpose, a hybrid approach was used, consisting of three selected MCDM/MCDA methods: DEMATEL, REMBRANDT, and VIKOR. The ranking was compared with the results achieved in the EIA report of the investment and the results were obtained by using a different set of MCDM/MCDA methods that were proposed in the first part of the research, i.e., AHP, Fuzzy AHP, TOPSIS, and PROMETHEE. The performed multi-criteria analyses allowed for an eventual multi-dimensional evaluation of the most popular MCDM/MCDA methods currently applied in the field of transport.

A Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm in Distribution Center Location Selection: A Case Study in Agricultural Supply Chain

Logistics is an important service sector, contributing to improving the competitiveness of the economy. Therefore, along with increasing the application of technology and effective business models, it is necessary to increase the connectivity of the infrastructure systems of industrial parks, roads, and seaports of regions and the country. Over the past decades, Vietnamese businesses have been step-by-step going through many stages from production, packaging, quality, hygiene, and safety to grasping new stages in the domestic and global value chain. In many industries, businesses are increasing the content of their own designs, exploiting brands, and approaching consumption networks in the target market. The role of the distribution center is becoming more and more important in ensuring a seamless and flawless supply chain. In particular, the distribution center is the most sensitive contact point between supply and demand in each enterprise. Therefore, the key mission of a distribution center is to reconcile supply and demand requirements. Distribution center location selection problems usually involve multiple quantitative and qualitative criteria that the decision maker must take into account for assessing the symmetrical impact of the criteria to reach the most accurate result. In this study, the authors propose a hybrid MCDM model based on Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm to support the distribution location selection problem of perishable agricultural products. The proposed model is then applied to the numerical case study of the sweet potato product of the Mekong Delta region of Vietnam to demonstrate the feasibility of the model. The contribution of this research is to propose an MCDM model for improving the efficiency of the agricultural supply chain through selecting a location distribution center. This proposed model can be applied to the agricultural supply chain around the world.

Fuzzy Optimization Model for Decision-Making in Supply Chain Management

Choosing a supplier is a complex decision-making process that can reduce the total cost of production inputs and increase profits without increasing the price or sacrificing product quality. However, supplier selection processes usually involve multiple quantitative and qualitative criteria which increase the complexity of the problem and may decrease the accuracy and effectiveness of the process. Such complex decision-making problems can be supported by using multicriteria decision-making (MCDM) models. While there have been multiple MCDM models to support supplier selection processes in different industries and sectors, only a few are developed to support the supplier selection processes in the garment industry, especially under uncertain decision-making environment. This paper presents an integrated mathematical model under a fuzzy environment and applies it to the supplier selection process in the garment industry. In this research, the authors utilize the Buckley extension based fuzzy Analytical Hierarchical Process (FAHP) method in combination with linear normalization based fuzzy Grey Relational Analysis (F-GRA) method to develop a MCDM approach to the supplier selection process under a fuzzy environment. As a result, supplier 08 (SA08) is the optimal supplier. The contribution of this work is to propose an MCDM model for ranking potential suppliers in the garment industry under a fuzzy environment. The proposed approach can also be applied to support complex decision-making processes under a fuzzy environment in different industries.

Identifying Factors for Selecting Land over Maritime in Inter-Regional Cross-Border Transport

Several cross-border land corridor projects have been implemented worldwide, because land transport is a vital alternative to international maritime transport in inter-regional transport. Maritime transport generally costs less than land transport, but it is much slower. Nonetheless, land transport can be more appropriate than maritime under certain situations. This study aims to identify factors that can help select between these two modes in long-distance inter-regional cross-border transport; to this end, a Tobit model is employed to estimate the dependent variable, i.e., the land ratio of origin–destination pairs between countries and/or areas. Eight variables are identified as significant: distance, export of manufacturing commodity, landlocked country/area, neighboring country/area, country risk, infrastructure level, port-access time, and maritime transport frequency. We also find that geographical conditions, country relationship, and regulations are barriers for selecting land transport. However, cross-border land corridors contribute to the increase of land ratio.

Revision of Sustainable Road Rating Systems: Selection of the Best Suited System for Hungarian Road Construction Using TOPSIS Method

There are a number of sustainable and environmentally friendly techniques and methods currently available in the construction industry. To promote sustainable development, different rating and certificating systems that evaluate the level of sustainability during the development of infrastructure construction projects have been developed. The aim of the research presented in this paper was to examine the applicability of sustainability rating systems in Hungary and find the most suitable option. After a review of commonly used rating systems, i.e., Greenroads, GreenLITES, I-LAST, Envision, and INVEST, the most suitable existing rating system is selected with the help of the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) mathematical decision analysis method. This was achieved by utilizing 12 categories of input data (weights) analyzed through TOPSIS. The input data (weights) of the TOPSIS method were determined by a small research group of industry experts and academic professionals based on Hungarian practices and methodology. As a result of the calculation, the study found that the Envision rating system satisfies the criteria best, closely followed by Greenroads.