Yazdani, Morteza, Zaraté, Pascale, Coulibaly, Adama and Kazimieras Zavadskas, Edmundas (2017) A group decision making support system in logistics and supply chain management. Expert systems with Applications, 88. pp. 376-392.

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Purpose: The 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. Methodology: The 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. Results: This 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/Originality: The 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.

Item Type: Article
Language: English
Date: 2017
Refereed: Yes
Uncontrolled Keywords: Group decision support system - Fuzzy linguistic variables - Logistic provider - Quality function deployment - Supply chain - Technique for order preference by similarity to ideal solution
Divisions: Institut de Recherche en Informatique de Toulouse
Site: UT1
Date Deposited: 17 Jan 2019 15:36
Last Modified: 02 Apr 2021 15:58
URI: https://publications.ut-capitole.fr/id/eprint/28501
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