Theory of fuzzy integrals and its applications

Despite the importance of decision-making (DM) techniques for construction of effective decision models for supplier selection, there is a lack of a systematic literature review for it. This paper provides a systematic literature review on articles published from 2008 to 2012 on the application of DM techniques for supplier selection. By using a methodological decision analysis in four aspects including decision problems, decision makers, decision environments, and decision approaches, we finally selected and reviewed 123 journal articles. To examine the research trend on uncertain supplier selection, these articles are roughly classified into seven categories according to different uncertainties. Under such classification framework, 26 DM techniques are identified from three perspectives: (1) Multicriteria decision making (MCDM) techniques, (2) Mathematical programming (MP) techniques, and (3) Artificial intelligence (AI) techniques. We reviewed each of the 26 techniques and analyzed the means of integrating these techniques for supplier selection. Our survey provides the recommendation for future research and facilitates knowledge accumulation and creation concerning the application of DM techniques in supplier selection.

Application of decision-making techniques in supplier selection: A systematic review of literature

Application of a new MCDA technique called MABAC.The MABAC sensitivity analysis.Five other MCDA techniques were tested under the same conditions.The MABAC showed stability and other techniques. This paper presents the application of the new DEMATEL-MABAC model in the process of making investment decisions on the acquisition of manipulative transport (Forklifts) in logistics centers. The DEMATEL method was used to obtain the weight coefficients of criteria, on the basis of which the alternatives were evaluated. The selection of criteria for evaluating Forklifts was based on an analysis of available literature. The evaluation and selection of Forklifts was carried out using a new multi-criteria method - the MABAC (Multi-Attributive Border Approximation area Comparison) method. This paper presents a practical application and a sensitivity analysis of the MABAC method. The sensitivity analysis was conducted in three stages. In the first stage, a stability analysis was carried out on the solution reached by the MABAC method, depending on changes made to the weights of the criteria. In the second and third stages, a consistency analysis of the results from the MABAC method was carried out depending on both the changes in the measurement units in which the values of individual criteria are presented and on the formulation of the criteria. The SAW, COPRAS, TOPSIS, MOORA and VIKOR methods were tested under the same conditions. Based on the results obtained, it was shown that the SAW, COPRAS, TOPSIS, MOORA and VIKOR methods do not meet one or more of the conditions set, while the MABAC method showed stability (consistency) in its solutions. Through the research presented in this paper, it is shown that the new MABAC method of multi-criteria decision-making is a useful and reliable tool for rational decision-making.

The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC)

Classification algorithm selection is an important issue in many disciplines. Since it normally involves more than one criterion, the task of algorithm selection can be modeled as multiple criteria decision making (MCDM) problems. Different MCDM methods evaluate classifiers from different aspects and thus they may produce divergent rankings of classifiers. The goal of this paper is to propose an approach to resolve disagreements among MCDM methods based on Spearman's rank correlation coefficient. Five MCDM methods are examined using 17 classification algorithms and 10 performance criteria over 11 public-domain binary classification datasets in the experimental study. The rankings of classifiers are quite different at first. After applying the proposed approach, the differences among MCDM rankings are largely reduced. The experimental results prove that the proposed approach can resolve conflicting MCDM rankings and reach an agreement among different MCDM methods.

https://www.worldscientific.com/doi/pdf/10.1142/S0219622012500095

Evaluation of classification algorithms using mcdm and rank correlation

An integrated green supplier selection approach with analytic network process and improved Grey relational analysis

https://ir.nctu.edu.tw:443/bitstream/11536/8208/1/000259485900013.pdf

Ruey Huei Yeh

Papers

Vendor selection by integrated fuzzy MCDM techniques with independent and interdependent relationships