Comparative Analysis of Robotic and Automatic Warehousing Systems with Fuzzy-Based Multi-Criteria Decision Making

Due to the increasing competition in the market, taking right decisions about the location selection for businesses is very important. The wrong choice of location for businesses may cause to large losses even bankruptcy. Textile sector is the first sector for which the location selection is quite important. The location selection of a textile factory is generally one of the most important decisions. The textile sector is considered the locomotive of domestic trade in Turkey. The purpose of this study is to describe the application of two Fuzzy Multi Criteria Decision Making (FMCDM) methods named Fuzzy TOPSIS and Fuzzy VIKOR for solving location selection problem of textile factor, which is located in Istanbul European side and looked for second location in Turkey. We used twelve criteria for FMCDM, which are determined from literatures and practical investigations. The methods of fuzzy set theory, linguistic value, Fuzzy TOPSIS and Fuzzy VIKOR are used to consolidate decision-makers? assessments about criteria weightings. Besides a sensitivity analysis is carried out for the Fuzzy TOPSIS method.

In today’s volatile and complex financial environment, decision-makers are often confronted with conflicting objectives, uncertain data, and vague human judgments. Traditional Multi-Criteria Decision Making (MCDM) methods, while useful, struggle to handle the inherent ambiguity present in many financial contexts. This paper explores the integration of Fuzzy Logic with MCDM techniques—collectively known as Fuzzy MCDM—to enhance the robustness and accuracy of financial decision-making. Applications such as investment portfolio selection, credit risk evaluation, capital budgeting, and mutual fund performance assessment are examined through the lens of hybrid fuzzy methodologies like Fuzzy AHP, Fuzzy TOPSIS, and Fuzzy VIKOR. By incorporating both qualitative and quantitative criteria, Fuzzy MCDM models offer a flexible, data-driven, and linguistically interpretable approach for financial analysis. The study highlights case examples and comparative results that demonstrate how Fuzzy MCDM tools improve decision quality in environments characterized by uncertainty and subjective judgment

PurposeThe objective of this paper is to present the employment of the new hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable business process outsourcing (BPO) decision.Design/methodology/approachThe paper explains the importance of selection criteria for evaluation of BPO. It then describes briefly the fuzzy hierarchical TOPSIS methodology. There then follows a discussion of the application of the fuzzy hierarchical TOPSIS with some sensitivity analysis to the BPO evaluation problem. Finally, some concluding remarks and perspectives are offered.FindingsUse of the hierarchical fuzzy TOPSIS methodology offers a number of benefits. It is a more systematic method than the other fuzzy multi‐criteria decision‐making (FMCDM) methods and it is more capable of capturing a human's appraisal of ambiguity when complex multi‐criteria decision‐making problems are considered. The hierarchical fuzzy TOPSIS is superior to the other FMCDM methods, such as fuzzy analytic hierarchy process (FAHP) and classical fuzzy TOPSIS methods, since the hierarchical structure without making pairwise comparisons among criteria, sub‐criteria, and alternatives is considered. Hierarchical fuzzy TOPSIS is an excellent tool to handle qualitative assessments about BPO evaluation problems, and its calculations are faster than FAHP. Also, hierarchical fuzzy TOPSIS makes it possible to take into account the hierarchical structure in the evaluation model. However, there are drawbacks. The classical fuzzy TOPSIS is a highly complex methodology and requires more numerical calculations in assessing the ranking order of the alternatives than the hierarchical fuzzy TOPSIS methodology and hence it increases the effort, thus limiting its applicability to real world problems.Originality/valueThe proposed model will be very useful to managers in the manufacturing sector, as this method makes decision making easier, systematic, efficient and effective.

Abstract. Six sigma method widely applied in production and service businesses is known as a project-oriented method. In six sigma method, selection of the prior project among others can be considered as a multi -criteria decision making problem. The conducted literature review has revealed that there is a large number of methods to select six sigma projects. It is more appropriate to use fuzzy multi-criteria decision making methods in project selection since evaluation criteria of six sigma projects include uncertainties. The aim of this study is to select the most appropriate project as a result of evaluating the projects by Fuzzy VIKOR, Fuzzy TOPSIS and Fuzzy COPRAS as methods of fuzzy multicriteria decision-making and integrating the ranking scores obtained from each method by Copeland method. The proposed method has been implemented in a large scale production company, operating in Aydin ASTIM Organized Industrial Zone. Keywords. Six Sigma Projects, Fuzzy VIKOR, Fuzzy TOPSIS, Fuzzy COPRAS, Fuzzy AHP, Copeland Method. JEL. M11, C44, L20, C02, D70, O22.

This study investigated outsourceable activities through fuzzy multi-criteria decision-making (FMCDM) techniques. The study, which involved five phases, relied on an integrated, exploratory research method. In phase 1, the qualitative method of meta-synthesis was used to identify the factors effecting outsourcing decisions. Next, the Delphi method was employed; in phase 3, questionnaires including paired comparisons of the items were submitted to 12 experts and the data gathered were analyzed through fuzzy analytical hierarchy process (FAHP). The importance rate of every criterion was then decided. In phase 4, following an investigation into the available documents and identification of nine outsourceable activities at an Iranian university, the data for analysis were collected through the questionnaires submitted to 12 experts. The data were then prioritized through fuzzy SAW, fuzzy TOPSIS and fuzzy VIKOR. Finally, given the fact that the results of these methods were conflicting, aggregate techniques, namely rank average, Borda and Copeland, were used to reach a consensus. As the findings revealed, the Medical Sector and Installation Affairs Department of the Sciences College and of the Humanities College showed the top ranks, followed by the Computer Affairs Department of the Sciences College and of the Humanities College, and the Veterinary Clinic, respectively. The study proposed a model for ranking outsourceable activities, suggesting that decision-makers and researchers would have to consider numerous criteria and several methods simultaneously for selecting outsourceable activities.

Since 2013, the Spanish fleet of EF-18 fighters has not received major updates nor any other jet has been proposed for their replacement. Thereby, a decision problem of interest to the Spanish Air Force is addressed in this study. In this regard, a collection of six potential alternatives (Eurofighter Typhoon, F-35 Lightning II, F/A-18 Super Hornet, Dassault Rafale, F-15 EX, and Saab 39 Gripen) and 14 criteria (3 of which being qualitative) are evaluated based on expert consensus by a combination of fuzzy logic and multi-criteria decision making (MCDM) approaches (AHP-VIKOR/AHP-TOPSIS). The weights of the criteria and the valuation of the qualitative ones (via questionnaires) were made possible by the participation of two independent groups of experts, all of them fighter pilots. Once the extraction of knowledge was carried out via a fuzzy version of a modified AHP, it was found that the two most important criteria (“air superiority over neighbor countries” and “tactical capability”) were qualitative. A comparison between the rankings of the alternatives provided by fuzzy VIKOR and fuzzy TOPSIS approaches highlights that the fuzzy VIKOR ranking appears highly influenced by the most important criteria. On the contrary, fuzzy TOPSIS presents a more compensatory behavior than fuzzy VIKOR. Given the differences observed when comparing such rankings of alternatives, a triple sensitivity analysis was conducted to ensure robustness. Our results highlight the Dassault Rafale as the most promising option for replacement. This finding suggests its potential as a benchmark for future fighter selection and next-generation fighter planning.

14 - Fuzzy decision making and its applications in cotton fibre grading

A Hybrid MCDM-DEA framework for optimal solar power plant site selection for Iran

A wide range of maturity models for product lifecycle management are proposed to assess the relative position of companies on their road to complete lifecycle systems' implementation. However, it is a tough job for the company to accurately make decisions of improving lifecycle systems' maturity due to the vague and complex data. The fuzzy VIKOR (Multi-criteria Optimization and Compromise Solution) is a compromise solution and has the ability of transfer subjective and implicit linguistics into objective and transparent data. An integrated fuzzy AHP (Analytic hierarchy process) and fuzzy VIKOR methodology is proposed to make a decision among option PLM strategies. The weights of the criteria called local weights are determined by fuzzy pairwise comparison matrices. The weights of alternatives with respect to criteria called global weights are calculated by fuzzy VIKOR. The final ranking weights are the overall analysis of local and global weights. A numerical example illustrates and clarifies the running steps of the proposed methodology. 2014 IEEE.

Our review paper research categorize the methods in the method of Fuzzy Multi-Criteria Decision Making (FMCDM) to find the method is widely used in the case of land clearing for plantation. Model FMCDM is used to assess the parameter in multi-criteria-based decision making. The dominant percentage of the result was obtained using Fuzzy Analytic Hierarchy Process (FAHP) method. While the application of other methods for the same problem are Fuzzy Ordered Weighted Averaging (FOWA), Fuzzy Elimination Et Choix Traduisant la Realite or Elimination and Choice Translating Reality (FELECTRE), Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), Fuzzy, Artificial Neural Networks (FANNs) has less. Some the research result also implemented hybrid in FMCDM Method to give some weight in the assessment of decision making. There was also a paper which integrates FMCDM to the GIS method on the land clearing. Therefore, it is concluded that the issue on the land clearing can be done through collaboration of several models of FMCDM, so that it can be developed by involving the decision model using multi-stakeholder model

A decision support system to evaluate the optimum fuel blend in an IC engine to enhance the energy efficiency and energy management

In recent years, environmental awareness has increased considerably, and in order to decrease endangerments such as air and water pollution, and also global warming, green procurement should be employed. Therefore, in the assessment of suppliers, their environmental performance should be taken into consideration along with other criteria for supplier selection. Raising awareness of sustainability in production and conservation and protection of the environment is very important both for the whole environment and for the company itself by increasing its competitive advantage. And, one of the steps to achieve this is for the companies to try to select green suppliers. So, the purpose of this study is to raise awareness and tackle the need for green supplier selection and, using multiple-criteria decision-making models, to elaborate a case study regarding this. A survey was conducted in a manufacturing firm. The data were analysed, and fuzzy MCDM (multicriteria decision-making) methods and artificial neural networks were implemented. Fuzzy methods are the fuzzy analytic hierarchy process (fuzzy AHP), fuzzy TOPSIS, and fuzzy ELECTRE. ANN supports the result of fuzzy MCDM models from the profit side. ANN can make the best estimate of the current year based on historical data. Fuzzy MCDM methods will also find good solutions using the available data but will produce different solutions as there are different decision-making methods. It is aimed to produce a synergy from the solutions obtained here and to produce a better solution. Instead of a single method, it would be more accurate to produce a better solution than the solution provided by all of them. The dominant result has been obtained using the committee fuzzy MCDM and ANN to select the best green supplier.

This study is motivated by the Zhuhai municipal government, which needs to select a sustainable ferry operator. Previous research has ignored the evaluation and selection of ferry operators. In addition, since ferry operator evaluation involves conflicting qualitative and quantitative criteria, and there may be uncertainty and ambiguity in the evaluation of criteria by experts, a fuzzy multi-criteria decision-making (MCDM) approach is required to address this challenge. To this end, this paper proposes an integrated MCDM framework model to evaluate and select the best ferry operator. First, a ferry operator evaluation index system with 15 sub-criteria is constructed according to literature and expert opinions; then the fuzzy analytic hierarchy process (FAHP) is used to determine the subjective weight of the criteria, and the entropy weight (EW) method is used to calculate the objective weight of the criteria. We use the linear weighting method to obtain the comprehensive weights of the criteria; finally, the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) method is adapted to determine the best ranking of the alternatives. This paper takes the Wanshan Islands in Zhuhai as a real case study to verify the proposed FAHP-EW-FTOPSIS method. The results show that the proposed method can be effectively applied to the evaluation and selection of ferry operators. Sensitivity analysis of criteria weights demonstrates the effectiveness and robustness of the proposed framework model. Key findings based on the research provide management insights that can benefit relevant stakeholders. This is the first paper to study the evaluation and selection of ferry operators. Hence, the evaluation index system and integrated framework model proposed in this paper can make important contributions to the evaluation of ferry operators.

The purpose of this study is to identify the criteria that are important for company owners operating in textile industry when selecting a manager. In order to determine these criteria, Multi-Criteria Decision Making (MCDM) techniques are uesd. In today's global and competitive market conditions, the selection of managers for company owners is a multivariate decision-making problem involving multiple criteria. In line with the purpose of the study, firstly, the criteria used in the selection of the managers were determined with a literature review. Four main criteria were determined by interviewing experts based on the determinant criteria. These criteria are determined as work experience, management skills, professional competence, and trust. These four criteria determined within the scope of the research were assessed by the company owners using linguistic variables. The weight of each criterion was determined by using the Fuzzy Analytical Hierarchy Process (FAHP) technique based on pairwise comparisons by means of linguistic variables. According to the results, it was determined that the most important criterion for manager selection in the textile industry is work experience. Then it was determined that trust, management skills, and professional competence came respectively. In the final stage of the implementation, a case study was performed using the fuzzy TOPSIS method and a sensitivity analysis and comparative comparison to check the robustness of the results. In order to test the validity of the proposed method, the decision problem is also analyzed with fuzzy EDAS and fuzzy SAW approaches. As a result, it has been determined that each method’s ranking result is similar and offers realistic solutions. From this perspective, the study presents a new model proposal to the literature as it uses the fuzzy EDAS and fuzzy SAW methods as well as the integrated fuzzy AHP and fuzzy TOPSIS methods in the selection of professional managers in textile industry. With the help of expert opinions in the textile sector, the study has shown that the selection of manager process can be easily solved with MCDM techniques and that the fuzzy TOPSIS method generates logical and reliable results

This study presents a synthesis on the application of multi-criteria decision making (MCDM) methodologies as an innovative tool to provide a more robust and reliable selection or ranking processes for health technology assessment (HTA). HTA is described as the 'systematic' evaluation of health related technologies with respect to multiple criteria. Thus, to carry out effective HTA processes, decision-makers should consider utilising integrated or hybrid decision making processes. In this study, we develop a decision support tool called 'DEMATSEL' which serves as an integrated MCDM methodology in fuzzy environments. Our integrated approach combines four widely-used MCDM methods, viz. fuzzy AHP, fuzzy TOPSIS, fuzzy VIKOR and goal programming. We demonstrate the effectiveness of our proposed novel approach on a fuzzy HTA case study of bariatric surgery selection in Turkey. [Submitted 4 July 2017; Revised 30 December 2017; Accepted 27 February 2018]