Fuzzy Multiple Criteria Decision Making Model Research Articles

Application of fermatean fuzzy weight operators and MCDM model DIBR-DIBR II-NWBM-BM for efficiency-based selection of a complex combat system

The use of complex automated combat systems is a basic feature of every modern combat operation, and all modern armies strive to implement such systems in their units. This paper investigates the choice of a complex combat system based on the efficiency criteria that condition it. The Defining Interrelationships Between Ranked criteria (DIBR) and the Defining Interrelationships Between Ranked criteria II (DIBR II) methods were used to determine the weight coefficients of the criteria, which proved to be effective in assessing the importance of each criterion in the context of making complex decisions. Aggregation of expert opinions, for each of the methods, was performed using the Normalized Weighted Bonferroni Mean (NWBM) operator. After the weight coefficients for both methods were obtained, the aggregation of the obtained values was performed using the Bonferroni Mean (BM) operator, which resulted in the final values of the weight coefficients of the criteria. In order to choose the optimal alternative, the Fermatean Fuzzy Weight Operators (FFWO) and BM operator were used. These operators contributed to the precise evaluation and ranking of alternatives, taking into account their characteristics and specificities. Furthermore, the paper analyzed the sensitivity of the output results to changes in the weight coefficients of the criteria. This is important in order to assess the stability of the Multiple Criteria Decision Making (MCDM) model and ensure its reliability in different scenarios. This work represents a significant contribution to the field of decision-making in this context and provides a useful framework for the selection of complex combat systems, and the combination of different methods and operators enables a comprehensive analysis and optimization of the research problem.

A rankability-based fuzzy decision making procedure for oil supplier selection

Multiple-criteria decision-making (MCDM) explicitly assesses several conflicting criteria for our daily lives in selecting products, vehicles, techniques, etc. Weighting on criteria is a critical step in MCDM as the invalid weight of criteria will lead to a wrong decision. The proposed method addresses some drawbacks of the entropy-based weighting method commonly used in MCDM. The proposed new weighting method considers multiple evaluation factors, including the performance of the decision-maker, the edge weight basis of a digraph, and dominance relationships in the data. By incorporating these factors, the proposed method overcomes the limitations of the entropy-based method and reduces the total computation required. We conducted experiments using sustainable transportation data and comprehensively analyzed the results. We also propose a fuzzy MCDM model incorporating the proposed weighting method and Dempster–Shafer theory. Our model aims to handle uncertainty and imprecision in decision-making. Finally, the correctness and effectiveness of the proposed model were tested on real-life applications. The results of these tests demonstrated that the proposed method provides a practical and effective approach to decision-making in various domains. Overall, the work introduces a new weighting method based on rankability in MCDM, addresses the limitations of the entropy-based method, and presents a fuzzy MCDM model for handling uncertainty. The experimental results suggest that the proposed approach is promising and offers valuable insights for decision-makers.

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.

APPLICATIONS OF FUZZY MULTIPLE CRITERIA DECISION MAKING METHODS IN CIVIL ENGINEERING: A STATE-OF-THE-ART SURVEY

A variety of fuzzy multiple criteria decision making (MCDM) models have been proposed to solve complicated decision-making problems. Many applications have been achieved, especially in the field of civil engineering. To analyze the developments about the fuzzy MCDM methods and their applications in civil engineering in recent years and further explore the future research directions, this study conducts a state of the art survey in which 52 journal papers focusing on the applications of fuzzy MCDM models in civil engineering from 2016 to 2020 are reviewed. We respectively classify these articles according to research problems and research methods. Through the literature review, we get findings in terms of the most concerned decision-making problem, the most widely-used evaluation criterion and the most popular fuzzy MCDM model. Furthermore, we present four aspects of research challenges and corresponding future research directions in the field of civil engineering, which may be helpful for researchers and practitioners to further investigate.

Ranking Alternatives with Relative Maximizing and Minimizing Sets in a Fuzzy MCDM Model

The final values of alternatives usually are fuzzy numbers in most decision making problems under uncertain environment. These fuzzy numbers need to be defuzzified by a ranking method to assist in decision making. Chen proposed ranking fuzzy numbers with maximizing set and minimizing set as an improvement on Jain’s maximizing set method. Liou and Wang indicated that ranking of any two fuzzy numbers by Chen’s method may be altered when xmax, xmin and k are changed. To solve this problem, Liou and Wang proposed ranking fuzzy numbers with integral value. However, the problem of Chen’s method remains. This work proposes relative maximizing and minimizing sets to improve upon Chen’s method. Comparative examples are provided to demonstrate advantages of the proposed ranking method, and an experiment is conducted to show its robustness. The proposed ranking method is applied to a fuzzy multiple criteria decision making (MCDM) model to present its applicability. Ranking procedure can be clearly displayed to enhance execution efficiency of the suggested fuzzy MCDM model. A numerical example is used to display feasibility of the proposed model. Finally, an experiment is investigated to show that the proposed ranking method improves upon Chen’s method in consistently ranking the final fuzzy numbers in the suggested fuzzy MCDM model.

Fuzzy multiple criteria decision-making via an inverse function-based total utility approach

This work presents ranking alternatives under fuzzy multiple criteria decision making (MCDM) via an inverse function-based total utility approach, where ratings of alternatives versus qualitative criteria as well as importance weights of all criteria are assessed in linguistic values represented by fuzzy numbers. Membership functions of the final fuzzy values of alternatives can be developed; some of their properties are investigated and proved. The right utility is obtained from the inverse function of right membership function of the final fuzzy value and the inverse function of maximizing set, while the left utility is obtained from the inverse function of left membership function of the final fuzzy value and the inverse function of minimizing set. Total utility is the sum of the right and left utilities. A larger total utility indicates that the corresponding alternative is more favorable. The ranking of fuzzy numbers can be clearly formulated to increase the applicability of the suggested fuzzy MCDM model. A numerical example demonstrates the feasibility of the proposed method, and some comparisons are provided to reveal robustness and advantages of the proposed method.

Strategizing for Better Life Development Using OECD Well-being Indicators in a Hybrid Fuzzy MCDM Model

Because gross domestic product is a deficient measure of well-being, designing well-being indicators has become a new international trend for informing government policies to better citizens’ lives. To facilitate achieving this goal, governments must establish sustainable, sufficient material living conditions and quality of life and attempt to understand citizens’ real needs. Given that analyzing well-being involves imprecise information, a fuzzy multiple criteria decision-making (MCDM) model is conducive to addressing the complex interrelationships among all indicators. Therefore, this paper proposes a hybrid fuzzy MCDM model that could facilitate strategizing for better life development. With aspiration levels based on the well-being indicators of the Organization for Economic Cooperation and Development, the proposed model combines the fuzzy DEMATEL technique, fuzzy DEMATEL-based analytic network process, and modified fuzzy VIKOR methods to process the interrelationships among all indicators and select the most pressing factors requiring improvement and development. A case study was used to demonstrate the effectiveness of the proposed fuzzy model. The empirical results attested that the proposed fuzzy model is superior to the traditional fuzzy model, identifying that for Taiwan, the “air pollution” criterion in the “environment” dimension is the most pressing issue to be addressed.

Evaluating evidence reliability based on intuitionistic fuzzy MCDM model

In this paper, the combination of unreliable evidence sources is considered based on multiple criteria decision making (MCDM) model in intuitionistic fuzzy environment. In the intuitionistic fuzzy MCDM framework, evidence sources can be evaluated based on the ranking method between intuitionistic fuzzy numbers. A generalized discounting operation on unreliable evidence bodies is firstly proposed to deal with uncertain reliability factors. Then we mainly investigate the evaluation evidence reliability factors without prior knowledge. Our proposed evaluation method is based on the principle of self-assessment. It is implemented by the probabilistic comparison between intuitionistic fuzzy values. Our proposed evaluation method is independent to the dissimilarity measure between basic probability assignments represented by an evidential distance. Numerical examples demonstrate the performance of our proposed reliability evaluation method.

Assessing customer value for express service providers: An empirical study from shippers’ perspective in Taiwan

Customer value is an important factor to evaluate the competitive strength for an international express service provider. It is also a key criterion to choose an express service. Hence, the main purpose of this paper was to develop a fuzzy multiple criteria decision-making (MCDM) model to assess the customer value for three express service providers in Taiwan based on the shippers’ perspective. Firstly we employed some concepts of fuzzy set theory to develop a fuzzy MCDM model. Subsequently, a hierarchical structure was constructed with four criteria, twenty sub-criteria and three alternatives (i.e. UPS, FedEx and DHL). Then, this paper conducts an empirical study by means of a survey from the viewpoints of shippers in Taiwan. Finally, the results of this study showed that: (1) the ‘time’ aspect is the most important criterion affecting the customer service based on the viewpoints of exporters and importers in Taiwan; (2) the top six key factors affecting customer value for express service providers are ‘land time between house and airport at both ends,’ ‘administrative processing time,’ ‘pick-up and haul time in warehouse,’ ‘level of accuracy,’ ‘level of safety,’ and ‘rapid turnover,’ respectively; (3) FedEx offers the best customer value in Taiwan based on the proposed fuzzy MCDM model. Furthermore, some discussions are provided for express service companies. The main contribution of this paper is to provide a practical survey for business application on customer value of express service providers.

Combination of unreliable evidence sources in intuitionistic fuzzy MCDM framework

In this paper, we consider the combination of unreliable evidence sources in multiple criteria decision making (MCDM) framework in intuitionistic fuzzy environment. In the intuitionistic fuzzy MCDM framework, evidence sources can be combined based on intuitionistic fuzzy aggregation operators when reliability factors are known. Generalized intuitionistic fuzzy aggregation operators are applied to combine evidence sources with intuitionistic fuzzy reliability factors. Discounting operation on unreliable evidence bodies is also extended to deal with uncertain reliability factors. Then we define a combination operation on intuitionistic fuzzy values to combine evidence bodies in the intuitionistic fuzzy MCDM model. Finally the estimation of the reliability factors without prior knowledge is studied. Our proposed evaluation method is based on the principle of self-assessment. It is implemented by the probabilistic comparison between intuitionistic fuzzy values. Moreover, the proposed evaluation method is independent of the dissimilarity measure between basic probability assignments. Numerical examples demonstrate the performance of our combination rules and reliability estimation method.

A Fuzzy Multiple-Criteria Decision-Making System for Analyzing Gaps of Service Quality

In a complex system, it is difficult to identify a specific aspect of the system in isolation to evaluate service quality. Based on the gap model of service quality, a fuzzy multiple-criteria decision-making (MCDM) model integrates the fuzzy analytic network process, the fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje in Serbian, and the improved importance–performance analysis (IPA) to provide a complete process to diagnose managerial strategies to reduce customer gaps in service quality efficiently. This fuzzy MCDM model has three significant advantages to deal with imprecise data, to simultaneously address relative customer preferences and relative customer gaps, and to improve the shortcomings in the traditional IPA. Furthermore, the case study of a cinema in Taiwan demonstrated the effectiveness and feasibility of the proposed model to diagnose managerial strategies for managers empirically.

Study on Location Selection of FMCG Logistics Centers Based on Fuzzy MCDM Model

To reduce logistics costs and enhance operation efficiency, selecting a suitable logistics center location has become a very important issue for manufacturing, sales and logistics industries. The selection of logistics centers is a most important decision owing to the need to consider various criteria that involve a complex decision process in which multiple requirements and uncertain conditions have to be taken into consideration simultaneously. In this paper, we propose a multiple criteria decision-making (MCDM) model based on fuzzy-set theory. And it is applied to the evaluation and selection of logistic centers. In the model, quantitative and qualitative criteria as well as the different importance weights of all the criteria are considered. A FMCG logistics center location example is used to elaborate how to use this model; meanwhile, the method is proved more scientific and reliable.

Select Optimal Chemical Detection Equipments Using Fuzzy Decision Making Method

The purpose of this research is to develop a universal model with a practical system to evaluate, identify and select an optimal system or device to perform the desired task from a large collection of available systems that have multiple objectives based on a fuzzy multiple criteria decision making model (FMCDMM). As an example, here we are using this research to identify and select an optimal detection system or device to detect hazardous chemical materials.

Select the Optimal Robots and Manipulators Using the Fuzzy Multi-Criteria Decision Making

The main purpose of this research is to develop a fuzzy multiple criteria decision making model (FMCDMM) to evaluate, identify and select an optimal robot system to perform the desired task from a large number of robot systems. A simple but effective weight estimation method is proposed in this paper in order to make a more objective and reliable estimation. The result of this research can be extended to any complicated system with multiple objectives. In this paper, we concentrate our discussion on selecting optimal robot systems used in manufacturing and production processes.

Evaluating real estate using a fuzzy MCDM approach

This paper suggests a fuzzy multiple criteria decision-making (MCDM) approach for the evaluation of real estates. The suggested approach considers both quantitative and qualitative criteria as well as different importance of the criteria. The final evaluation values from the suggested fuzzy MCDM approach are still fuzzy numbers. A ranking method is needed to defuzzify these fuzzy numbers to complete the approach. In this paper, Chen’s maximising set and minimising set is improved to resolve its ranking inconsistencies via numerical comparison. The improved ranking method is then applied to defuzzify the final fuzzy evaluation values to help perform decision making. Formulas for the ranking procedure can be clearly developed, which bridge the fuzzy MCDM model and the defuzzification process to complete the approach. The suggested approach can be regarded as a decision making system, which is flexible and can be customised to the needs and requirements of the interested parties.

Aviatic innovation system construction using a hybrid fuzzy MCDM model

Due to the occurrence of several recent threats, such as, from an international perspective, SARS, the 9/11 terrorist attack, increases in the price of oil, depressions in the economy, and, from a domestic perspective, increasing interaction with China, joining the WTO, low railway prices, and high-speed rail development, resulting in passenger rate dropping drastically, an increasing number of Taiwanese airlines have been facing deficits or closing down in recent years. Therefore, long-term strategies for gaining a competitive advantage are now starting to focus on innovation rather than cost reduction. Although attention to the importance of innovation is rising, there are few studies today that provide airlines with a clear and precise way to successfully conduct innovation operations. The aim of this study is to solve this dilemma by constructing a novel aviatic innovation system (AIS). In this paper, a hybrid fuzzy multiple criteria decision-making (MCDM) model based on a fuzzy analytical hierarchical process (FAHP) and a VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is adopted to complete the construction of the AIS. The value of the AIS is to provide Taiwanese airlines with innovation-oriented techniques for future strategy development. We believe that the AIS can contribute to the survival of Taiwanese airlines in the near future.

Application of a combined fuzzy multiple criteria decision making and optimization programming model to the container transportation demand split

The container transportation demand split is one of the most important decision issues for government transportation departments and port organizations. In previous studies, many researchers assumed that the shipping carrier would aim to minimize the total operation cost by selecting an appropriate port as the most favorable one to call, and the shipper would aim to minimize the inland freight cost by selecting the nearest port as the most favorable one to import and export international trade containers. Thus, a number of mathematical programming models have been developed. But in practice, the shipping carrier not only aims to minimize the total operation cost but also takes into account other criteria such as the volume of containers and port facility conditions when choosing an appropriate port as the most favorable one to call. The shipper not only aims to minimize the inland freight cost but also takes into account the frequency of ship callings when choosing an appropriate port as the most favorable one to import and export international trade containers. Thus, the purpose of this paper is to formulate a combined fuzzy multiple criteria decision making and optimization programming model for solving the container transportation demand split problem. There are two stages in this combined model: in stage one, we first compute the container transportation demand split rate by using fuzzy multiple criteria decision making (MCDM) method; whereas in stage two, an optimization mathematical programming network model is proposed for determining the inland origin destination (O-D) of import/export containers. The utilization of the proposed model is demonstrated with a case of Taiwanese ports. The results show that the proposed combined fuzzy MCDM and optimization programming model can be used to explain the container transportation demand split practice.

Applying maximizing set and minimizing set to solving a tradeoff based fuzzy MCDM model

This paper suggests a tradeoff based fuzzy multiple criteria decision making (MCDM) model, where criteria are categorized to benefit qualitative, benefit quantitative and cost quantitative ones. The membership function of the final fuzzy evaluation value of each alternative can be developed. All the final fuzzy evaluations are defuzzified via the ranking approach of maximizing set and minimizing set. Ranking procedure can be clearly formulated, making the decision making execution more efficient.

Application of FMCDM model to selecting the hub location in the marine transportation: A case study in southeastern Asia

Hub location selection problems have become one of the most popular and important issues not only in the truck transportation and the air transportation, but also in the marine transportation. The main focus of this paper is on container transshipment hub locations in southeastern Asia. Transshipment is the fastest growing segment of the containerport market, resulting in significant scope to develop new transshipment terminal capacity to cater for future expected traffic flows. A shipping carrier not only calculates transport distances and operation costs, but also evaluates some qualitative conditions for existing hub locations and then selects an optimal container transshipment hub location in the region. In this paper, a fuzzy multiple criteria decision-making (FMCDM) model is proposed for evaluating and selecting the container transshipment hub port. Finally, the utilization of the proposed FMCDM model is demonstrated with a case study of hub locations in southeastern Asia. The results show that the FMCDM model proposed in this paper can be used to explain the evaluation and decision-making procedures of hub location selection well. In addition, the preferences are calculated for existing hub locations and these are then compared with a new proposed container transshipment hub location in the region, in this instance the Port of Shanghai. Furthermore, a sensitivity analysis is performed.

Application of fuzzy MCDM to priority setting in agricultural biotechnology industries

Following in the wake of medical biotechnology, agricultural biotechnology (AgBio) is slated to become a key area of development in the biotechnology industry. Because agricultural biotechnology is closely connected with food, health, and resource technology industries, many countries are investing heavily in terms of both funding and talent to enhance their international competitiveness in this field. This research study was designed using the fuzzy multiple criteria decision making (FMCDM) model combining analytic hierarchy process (AHP) and fuzzy theory and holding a specialists’ conference to decide promising AgBio products with international competitiveness for use in guiding industrial development strategies and the allocation of R&D resources. The results show that the FMCDM model can effectively summarize the views of AgBio specialists for the purpose of selecting promising target industries. The research process was also used to explore the various target industries and assess key issues such as the causal relationship between criteria and industries’ degree of development. Beyond helping decision-makers formulate policies and allocate resources, this information is also provided as a research reference in connection with market surveys and industrial development trends, etc.