Morteza Yazdani

New integration of MCDM methods and QFD in the selection of green suppliers

AbstractCurrently, topics of operations management and supply chain systems have been gaining more interest of researchers. Efficiency in supply chain activities and operations management firstly benefit organisations. One of the main operations in supply chain systems is the collaboration with selected suppliers. Various models have been proposed in terms of supplier evaluation and selection studies. The invention of a new integrated frame for the building of an effective supplier evaluation system is a multi-attribute task that consists of several factors as external and internal variables. This paper delivers a creative integrated model of supplier selection problem using SWARA, QFD and a new MCDM tool called WASPAS. This work considers customer attitudes in the process of supplier evaluation. To give more weight to customer requirements, a new SWARA method has been designed; additionally, QFD and the house of quality matrix have been used to transform customer requirements into the supplier evaluation...

VIKOR and its Applications: A State-of-the-Art Survey

Recently, Multiple-Criteria Decision Making (MCDM) tools have increasingly been expanded to help researchers and practitioners to evaluate and select the best compromise alternatives. Among popular MCDM methods, Vlsekriterijumska Optimizacija I KOmpromisno Resenje (VIKOR) has attracted much attention to cope with complex problems with conflict factors. The current study conducted a state-of-the-art literature review to embody the research on VIKOR and its applications. The paper structure consists of 198 papers from more than 100 journals and conference proceedings since 2002 which were classified into nine categories: 1) Design and manufacturing management, 2) Business and marketing management, 3) Supply chain and logistics management, 4) Environmental resources and energy management, 5) Construction management, 6) Education management, 7) Health-care and risk management, 8) Tourism management, and 9) Other topics. The last topic contains Information and knowledge management, Mine industry, etc. The study also proposes four classifications: 1) Publication year, 2) Journals, 3) other techniques combined or compared with VIKOR, and 4) Keywords distribution by VIKOR papers specifications. Finally, it was proposed forthcoming areas of study and recommendations for practical means. This study intends to generate insights on decision making techniques.

Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection

AbstractEvaluation based on Distance from Average Solution (EDAS) is a new multicriteria decision making (MCDM) method, which is based on the distances of alternatives from the average scores of attributes. Classical EDAS has been already extended by using ordinary fuzzy sets in case of vague and incomplete data. In this paper, we propose an interval-valued intuitionistic fuzzy EDAS method, which is based on the data belonging to membership, nonmembership, and hesitance degrees. A sensitivity analysis is also given to show how robust decisions are obtained through the proposed intuitionistic fuzzy EDAS. The proposed intuitionistic fuzzy EDAS method is applied to the evaluation of solid waste disposal site selection alternatives. The comparative and sensitivity analyses are also included.

An application of an integrated ANP–QFD framework for sustainable supplier selection

ABSTRACT This study provides a novel integrated multi-criteria decision-making approach to sustainable supplier selection problems. Despite the large supply chain management literature on green performance measurement, the need for a systematic analysis of how specific sustainable variables develop and affect each other remains mostly overlooked. The proposed integrated framework allows for such an analysis. By combining analytic network process and quality function deployment, our model identifies a clear hierarchical structure for all the relevant sustainable factors and sub-factors while weighting the decision criteria based on the importance given to customer requirements. Finally, suppliers are ranked using a multi-objective optimisation procedure based on ratio analysis and weighted aggregated sum product assessment. The proposed framework is used to analyse a case study of a dairy company, but it can be easily implemented for supplier selection by any other company with similar features.

A group decision making support system in logistics and supply chain management

Logistic provider selection is Multi-Criteria Decision-Making problem.Selection of the best alternative depends on opinion of the group stakeholders.Criteria values are determined in linguistic terms and real use of DSS presented.Basis of the developed DSS is the second most popular MCDM method TOPSIS-F.The investigation carried out under a European Commission project. PurposeThe paper proposes a decision support system for selecting logistics providers based on the quality function deployment (QFD) and the technique for order preference by the similarity to ideal solution (TOPSIS) for agricultural supply chain in France. The research provides a platform for group decision making to facilitate decision process and check the consistency of the outcomes. MethodologyThe proposed model looks at the decision problem from two points of view considering both technical and customer perspectives. The main customer criteria are confidence in a safe and durable product, emission of pollutants and hazardous materials, social responsibility, etc. The main technical factors are financial stability, quality, delivery condition, services, etc. based on the literature review. The second stage in the adopted methodology is the combination of quality function deployment and the technique for order preference by similarity to ideal solution to effectively analyze the decision problem. In final section we structure a group decision system called GRoUp System (GRUS) which has been developed by Institut de Recherche en Informatique de Toulouse (IRIT) in the Toulouse University. ResultsThis paper designs a group decision making system to interface decision makers and customer values in order to aid agricultural partners and investors in the selection of third party logistic providers. Moreover, we have figured out a decision support system under fuzzy linguistic variables is able to assist agricultural parties in uncertain situations. This integrated and efficient decision support system enhances quality and reliability of the decision making. Novelty/OriginalityThe novelty of this paper is reflected by several items. The integration of group multi-criteria decision tools enables decision makers to obtain a comprehensive understanding of customer needs and technical requirements of the logistic process. In addition, this investigation is carried out under a European commission project called Risk and Uncertain Conditions for Agriculture Production Systems (RUC-APS) which models risk reduction and elimination from the agricultural supply chain. Ultimately, we have implemented the decision support tool to select the best logistic provider among France logistics and transportation companies.

An integrated fuzzy ANP–QFD approach for green building assessment

One of the major concerns in the construction industry is the sustainability of building projects. There are various trade-offs between functionality and design, which often lead to an issue of whether sustainably designed buildings would meet stakeholder requirements. This paper provides a novel integrated structure for assessing green buildings realistically based on stakeholders’ fuzzy preferences. In particular, the paper uses the analytic network approach (ANP) to evaluate the correlation matrices in a quality function deployment (QFD) framework. A case study on green building index assessment in Malaysia illustrates the proposed integrated method. Sensitivity analysis validated the customerstakeholder agreement towards the design of the green building. Cluster analysis was also used to group design specifications prior to the analysis.

Nonlinear genetic-based model for supplier selection: a comparative study

AbstractEvaluation and selection of candidate suppliers has become a major decision in business activities around the world. In this paper, a new hybrid approach based on integration of Gene Expression Programming (GEP) with Data Envelopment Analysis (DEA) (DEA-GEP) is presented to overcome the supplier selection problem. First, suppliers’ efficiencies are obtained through applying DEA. Then, the suppliers’ related data are utilized to train GEP to find the best trained DEA-GEP algorithm for predicting efficiency score of Decision Making Units (DMUs). The aforementioned data is also used to train Artificial Neural Network (ANN) to predict efficiency scores of DMUs. The proposed hybrid DEA-GEP is compared to integrated approach of Artificial Neural Network with Data Envelopment Analysis (DEA-ANN) to support the validity of the proposed model. The obtained results clearly show that the model based on GEP not only is more accurate than the DEA-ANN model, but also presents a mathematical function for efficien...

An extended stepwise weight assessment ratio analysis (SWARA) method for improving criteria prioritization process

The process of criteria prioritization and weighting is an important part of multiple attributes decision making. The most frequently applied multi-attribute decision-making weighting tools include analytical hierarchy process, stepwise weight assessment ratio analysis, factor relationship, and best–worst method. When policies are at the core of decision making, stepwise weight assessment ratio analysis method is the most efficient method for criteria evaluation. It involves two important steps: the first is to prioritize the criteria by consulting experts, while the second is the weighting process. This research seeks to extend stepwise weight assessment ratio analysis to improve the quality of the decision-making process by incorporating the reliability evaluation of experts’ idea into the first step. Such a component is absent from the first step in all other similar models. Thus, an extended version of stepwise weight assessment ratio analysis can be applied for such evaluation. To test the applicability and performance of the proposed method, a numerical example from an earlier study was used. The proposed version can replace the classic version in future studies as an improved method in decision-making area.

Application of MCDM Techniques on Nonconventional Machining of Composites

This study has been carried out to assess the impact of electrical discharge machining parameters on the SiC-reinforced aluminum metal matrix composites. The criteria in machining process including electrodes material, current, pulse time, and dielectric medium were diversified to evaluate their effect on material removal rate (MRR), surface roughness (SR), and residual stresses. The residual stresses induced due to subsequent heating and cooling shocks during the electric discharge process are of primary concern while machining process. The magnitude of residual stresses induced on the machined surface was estimated via X-ray diffraction method. The process conditions that influenced the responses were recognized and optimized synchronically using multiple criteria decision-making and statistical techniques. In this study, analytical hierarchy process (AHP) and a multi-objective optimization analysis (MOORA) will solve process condition problem. This approach confers the combination of process parameter settings suitable for the machining of such composites.

Intelligent Decision Making Tools in Manufacturing Technology Selection

The importance of technology in modern companies is literally growing. Technology protects the natural environment and acts as catalyst toward a more productive economy. Technology development has been the most demanding activity in industrial sectors over years and technology selection and implementation is one of the acknowledged projects in many companies. There are many factors influencing the problem of evaluating and choosing a new technology. Therefore, manufacturing operation managers are involved in a decision-making system with conflicting elements in their selection process. In this condition, application of multi-attribute decision-making (MADM) tools is highly recommended. This study examines the utilization of analytic hierarchy process and an adopted MADM method named CoCoSo to simultaneously determine the importance of decision factors and obtain the optimal ranking. At the final stage, we configure a sensitivity analysis to check and examine the accuracy of the results and performance of the present decision system. The study corresponds to a case study of choosing best packaging technology for a dairy company.