An integrated fuzzy MCDM approach for supplier evaluation and selection

A fuzzy multi-criteria group decision making approach that makes use of quality function deployment (QFD), fusion of fuzzy information and 2-tuple linguistic representation model is developed for supplier selection. The proposed methodology seeks to establish the relevant supplier assessment criteria while also considering the impacts of inner dependence among them. Two interrelated house of quality matrices are constructed, and fusion of fuzzy information and 2-tuple linguistic representation model are employed to compute the weights of supplier selection criteria and subsequently the ratings of suppliers. The proposed method is apt to manage non-homogeneous information in a decision setting with multiple information sources. The decision framework presented in this paper employs ordered weighted averaging (OWA) operator, and the aggregation process is based on combining information by means of fuzzy sets on a basic linguistic term set. The proposed framework is illustrated through a case study conducted in a private hospital in Istanbul.     

Application of fuzzy analytic network process for supplier selection in a manufacturing organisation

The contemporary manufacturing organisations are forced to adopt advanced manufacturing paradigms for sustaining in the global markets. Supply chain management is an essential ingredient of advanced manufacturing systems since outsourcing gains vital importance. Supplier selection is a vital issue concerned in the process of managing global supply chains. A conceptual model for supplier selection encompassing various criteria and sub-criteria has been developed. In this article, fuzzy analytic network process (fuzzy ANP) approach has been used for the supplier selection process. The case study has been carried out in an Indian electronics switches manufacturing company. Based on supplier selection weighted index, the best supplier has been determined. This is followed by the conduct of sensitivity analysis as well as questionnaire-based validation. The results of the validation study indicated that the application of fuzzy ANP is practically feasible and adaptable in the contemporary industrial scenario.     

An intelligent approach to machine tool selection through fuzzy analytic network process

In this study, we utilize analytic network process (ANP), a more general form of AHP, for justifying stand-alone machine tools out of available alternatives in market due to the fact that AHP cannot accommodate the variety of interactions, dependencies and feedback between higher and lower level elements. However, due to the vagueness and uncertainty on judgments of a decision-maker, the crisp pair wise comparison in the conventional ANP seems to be insufficient and imprecise to capture the right judgments of the decision-maker. That is why, also in this paper, fuzzy number logic is introduced in the pair wise comparison of ANP to make up for this deficiency in the ANP. In short, here, an intelligent approach to machine tool selection (MTS) problem through fuzzy ANP is proposed to improve the imprecise ranking of company’s requirements which is based on the conventional ANP. In order to reach to final solution, a preference ratio (PR) analysis is done by using the results of the fuzzy ANP, and investment costs of alternatives. In addition, a numerical example is presented to illustrate the proposed approach.     

An ERP software selection process with using artificial neural network based on analytic network process approach

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to fact that it considers criteria and sub criteria relations and interrelations in selecting the software.Opinions of many experts are obtained while building ANP model for the selection ERP then opinions are reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert’s opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation.An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision.     

A hybrid approach to concept selection through fuzzy analytic network process

Evaluating conceptual design alternatives in a new product development (NPD) environment has been one of the most critical issues for many companies which try to survive in the fast-growing world markets. Therefore, most companies have used various methods to successfully carry out this difficult and time-consuming evaluation process. Of these methods, analytic hierarchy process (AHP) has been widely used in multiple-criteria decision-making (MCDM) problems. But, in this study, we used analytical network process (ANP), a more general form of AHP, instead of AHP due to the fact that AHP cannot accommodate the variety of interactions, dependencies and feedback between higher and lower level elements. Furthermore, in some cases, due to the vagueness and uncertainty on the judgments of a decision-maker, the crisp pairwise comparison in the conventional ANP is insufficient and imprecise to capture the right judgments of the decision-maker. Therefore, a fuzzy logic is introduced in the pairwise comparison of ANP to make up for this deficiency in the conventional ANP, and is called as fuzzy ANP. In short, in this paper, a fuzzy ANP-based approach is proposed to evaluate a set of conceptual design alternatives developed in a NPD environment in order to reach to the best one satisfying both the needs and expectations of customers, and the engineering specifications of company. In addition, a numerical example is presented to illustrate the proposed approach.     

Fuzzy analytic hierarchy process and analytic network process: An integrated fuzzy logarithmic preference programming

This paper proposes a two-stage fuzzy logarithmic preference programming with multi-criteria decision-making, in order to derive the priorities of comparison matrices in the analytic hierarchy pprocess (AHP) and the analytic network process (ANP). The Fuzzy Preference Programming (FPP) proposed by Mikhailov and Singh [L. Mikhailov, M.G. Singh, Fuzzy assessment of priorities with application to competitive bidding, Journal of Decision Systems 8 (1999) 11–28] is suitable for deriving weights in interval or fuzzy comparison matrices, especially those displaying inconsistencies. However, the weakness of the FPP is that it obtains priorities of comparison matrices by additive constraints, and generates different priorities by processing upper and lower triangular judgments. In addition, the FPP solves the comparison matrix individually. By using multiplicative constraints, the method proposed in this paper can generate the same priorities from upper and lower triangular judgments with crisp, interval or fuzzy values. Our proposed method can solve all of the matrices simultaneously by multiple objective programming. Finally, five examples are demonstrated to show the proposed method in more detail.     

基于可拓模糊层次分析的异构网络选择算法

针对目前异构网络选择算法在确定指标权重存在主观性的问题,提出基于可拓模糊层次分析的异构无线网络选择算法。该算法在分析不同业务类型对网络性能需求的基础上,结合可拓理论,将收集到的性能参数映射到性能标度区间中,通过网络物元模型的建立和相对隶属度的计算,构建了新的判决矩阵,利用模糊层次分析法计算网络性能参数的综合权重。最后,通过对相对隶属度的加权排序,得到最优接入网络。仿真实验证明:该方法能综合考虑不同用户的业务类型和网络的客观性能,提高了异构网络中多模终端选择网络的准确性和有效性。     

An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management

Supplier selection is an important issue in supply chain management. In recent years, determining the best supplier in the supply chain has become a key strategic consideration. However, these decisions usually involve several objectives or criteria, and it is often necessary to compromise among possibly conflicting factors. Thus, the multiple criteria decision making (MCDM) becomes a useful approach to solve this kind of problem. Considering both tangible and intangible criteria, this study proposes integrated fuzzy techniques for order preference by similarity to ideal solution (TOPSIS) and multi-choice goal programming (MCGP) approach to solve the supplier selection problem. The advantage of this method is that it allows decision makers to set multiple aspiration levels for supplier selection problems. The integrated model is illustrated by an example in a watch firm.     

Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem

Supplier selection is nowadays one of the critical topics in supply chain management. This paper presents a new decision making approach for group multi-criteria supplier selection problem, which clubs supplier selection process with order allocation for dynamic supply chains to cope market variations. More specifically, the developed approach imitates the knowledge acquisition and manipulation in a manner similar to the decision makers who have gathered considerable knowledge and expertise in procurement domain. Nevertheless, under many conditions, exact data are inadequate to model real-life situation and fuzzy logic can be incorporated to handle the vagueness of the decision makers. As per this concept, fuzzy-AHP method is used first for supplier selection through four classes (CLASS I: Performance strategy, CLASS II: Quality of service, CLASS III: Innovation and CLASS IV: Risk), which are qualitatively meaningful. Thereafter, using simulation based fuzzy TOPSIS technique, the criteria application is quantitatively evaluated for order allocation among the selected suppliers. As a result, the approach generates decision-making knowledge, and thereafter, the developed combination of rules order allocation can easily be interpreted, adopted and at the same time if necessary, modified by decision makers. To demonstrate the applicability of the proposed approach, an illustrative example is presented and the results analyzed.     

A fuzzy analytic network process based approach to transportation-mode selection between Turkey and Germany: A case study

A case study examining the different modes for transportation of freight by a Turkish logistics-service provider company is presented herein. A number of conflicting qualitative and quantitative criteria exist for evaluating alternative modes of transport. Qualitative criteria are often accompanied by ambiguity and vagueness. To cope with ambiguity and vagueness problem, the fuzzy analytic network process (ANP) method has been used. A large number of detailed criteria that interact with each other have been evaluated and synthesized to obtain the most suitable transportation mode. This evaluation has been carried out by a group of decision makers coming from different management levels and functional areas in the sector of logistics and from the service company with intent to provide a more accurate and mutually acceptable solution. Furthermore, the model used here has been validated by comparing the results obtained with the current preferences of the company.     

基于层次分析法的模糊分类优选模型

不同的模糊分类算法在同一个数据集合上常会产生不同的模糊分类．究竟哪种方法最能揭示数据的真实结构，对此，以模糊分类有效性指标为评价指标，应用层次分析法对各模糊分类进行综合评价，建立了一个模糊分类优选模型．大量实验表明，该优选模型所选出的最优模糊分类，其模式识别率高，能揭示数据的真实结构．     

A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach

This study presents a strategy-aligned fuzzy simple multiattribute rating technique (SMART) approach for solving the supplier/vendor selection problem from the perspective of strategic management of the supply chain (SC). The majority of supplier rating systems obtained their optimal solutions without considering firm operations management (OM)/SC strategy. The proposed system utilizes OM/SC strategy to identify supplier selection criteria. A fuzzy SMART is applied to evaluate the alternative suppliers, and deals with the ratings of both qualitative and quantitative criteria. The final decision-maker incorporates the supply risks of individual suppliers into final decision making. Finally, an empirical study is conducted to demonstrate the procedure of the proposed system and identify the suitable supplier(s).     

A fuzzy solution approach for multi objective supplier selection

In today’s severe competitive environment the selection of appropriate suppliers is a significantly important decision for effective supply chain management. Appropriate suppliers reduce purchasing costs, decrease production lead time, increase customer satisfaction and strengthen corporate competitiveness. In this study a multiple sourcing supplier selection problem is considered as a multi objective linear programming problem. Three objective functions are minimization of costs, maximization of quality and maximization of on-time delivery respectively. In order to solve the problem, a fuzzy mathematical model and a novel solution approach are proposed to satisfy the decision maker’s aspirations for fuzzy goals. The proposed approach can be efficiently used to obtain non-dominated solutions. A numerical example is given to illustrate how the approach is utilized.     

Modeling risk based maintenance using fuzzy analytic network process

The study deals with the problem of maintenance policy selection for an industrial unit. Maintenance policy selection is a multiple criteria decision making problem. Criteria considered here are ‘risk of equipment failure’ and the ‘cost of maintenance’. The maintenance policies considered are Corrective Maintenance (CM), Time Based Maintenance (TBM), Condition Based Maintenance (CBM) and Shutdown Maintenance (SM). For modeling, fuzzy analytic network process (FANP) has been employed. Chang’s extended analysis has been applied to deal with the fuzzy variables and the preferred maintenance policy alternative is found out using FANP analysis. The methodology was applied to a unit of a chemical plant and the suitable maintenance policy was found out for each of the 13 equipment of the unit. The results were compared to the earlier study using Analytic Hierarchal Process and Goal Programming (Arunraj and Maiti, 2010) vis-a-vis the existing practices. The results show that CBM is preferred when the risk possessed by an equipment is very high while CM is preferred in those cases where risk is low and cost is the main consideration. But in cases where both cost and risk are somewhat equally important, TBM is the preferred option.     

Revisiting the supplier selection problem: An integrated approach for group decision support

Decision support for supplier selection is a highly researched theme in procurement management literature. However applications of group decision support theories are yet to be explored extensively in this domain. This study proposes an approach for group decision support for the supplier selection problem by integrating fuzzy Analytic Hierarchy Process (AHP) for group decision making and fuzzy goal programming for discriminant analysis. In the first step, the fuzzy AHP theory with the Geometric Mean Method has been used to prioritize and aggregate the preferences of a group of decision makers. Then consensus has been developed between these aggregated priorities using the Ordinal Consensus Improvement Approach. Subsequently, the consensual priorities of this group of decision makers have been integrated with fuzzy goal programming theory for discriminant analysis to provide predictive decision support. Finally it has been shown through a case study how the integrated approach using fuzzy AHP for group decision making and fuzzy goal programming with soft constraints has been more effective as compared to an existing approach for group decision making using only AHP.     

An integrated fuzzy MCDM based approach for robot selection considering objective and subjective criteria

Robots with vastly different capabilities and specifications are available for a wide range of applications. Selection of a robot for a specific application has become more complicated due to increase in the complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. The aim of this paper is to present an integrated approach for the optimal selection of robots by considering both objective and subjective criteria. The approach utilizes Fuzzy Delphi Method (FDM), Fuzzy Analytical Hierarchical Process (FAHP), Fuzzy modified TOPSIS or Fuzzy VIKOR and Brown–Gibson model for robot selection. FDM is used to select the list of important objective and subjective criteria based on the decision makers’ opinion. Fuzzy AHP method is then used to find out the weight of each criterion (both objective and subjective). Fuzzy modified TOPSIS or Fuzzy VIKOR method is then used to rank the alternatives based on objective and subjective factors. The rankings obtained are used to calculate the robot selection index based on Brown–Gibson model. The proposed methodology is illustrated with a case study related to selection of robot for teaching purpose. It is found that the highest ranked alternative based on Fuzzy VIKOR is closest to the ideal solution.     

An integrated fuzzy-lp approach for a supplier selection problem in supply chain management

In supply chain management process, the firm select best supplier takes the competitive advantage to other companies. Thus, supplier selection is an important issue and with the multiple criteria decision-making approach, the supplier selection problem includes both tangible and intangible factors. This paper is aimed to present an integrated fuzzy and linear programming approach to the problem. Firstly, linguistic values expressed in trapezoidal fuzzy numbers are applied to assess weights and ratings of supplier selection criteria. Then a hierarchy multiple model based on fuzzy set theory is expressed and fuzzy positive and negative ideal solutions are used to find each supplier’s closeness coefficient. Finally, a linear programming model based on the coefficients of suppliers, buyer’s budgeting, suppliers’ quality and capacity constraints is developed and order quantities assigned to each supplier according to the linear programming model. The integrated model is illustrated by an example in a textile firm.