Multi-Criteria Decision-Making Methods in Green Logistics

Author:

Osintsev N. A.1

Affiliation:

1. Nosov Magnitogorsk State Technical University (NMSTU)

Abstract

Due to the increased demands of the world community in accordance with the goals of the concept of sustainable development, supply chain management requires complex decisionmaking models that consider many environmental, economic, and social constraints when implementing various environmentally friendly, green methods and technologies. An effective tool in such conditions is the use of MCDM, multi-criteria decision-making methods. The objective of the research, the results of which are provided in the article, is to analyse the application of MCDM in green logistics and management of green supply chains. The work used a set of methods including system and structural-functional analysis, methods of the theory of fuzzy sets, mathematical statistics, and expert assessments. A general scheme of MCDM implementation is offered and a combined MCDM model is developed for assessing decisions on the choice of green technologies, including a system of indicators for logistics flows, a model for managing logistics flows and a system of tools for green logistics. In the MCDM model, a fuzzy analytical hierarchical process (fuzzy AHP) is used to establish the weight of indicators of logistics flows, eleven MCDM methods are used to rank green logistics tools: SAW, TOPSIS, PROMETHEE, COPRAS, ARAS, WASPAS, MAIRCA, EDAS, MABAC, CODAS, MARCOS. Comparison of the use of various MCDM methods showed a high convergence of the ranking results (Spearman’s rank correlation coefficient is of 0.949). The most consistent are SAW, MARCOS and WASPAS methods, the least consistent are CODAS methods. The results of the design example showed that the most preferable solution is the «use of intermodal technologies and multimodal transportation» (ranked first within all eleven methods), the least preferable solution is the «use of environmentally friendly fuels and lubricants (fuels)» (ranked 12th within 10 methods of 11).

Publisher

FSBEO HPE Moscow State University of Railway Engineering (MIIT)

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