1. A FUZZY DECISION-MAKING APPROACH FOR EVALUATION AND SELECTION OF THIRD PARTY REVERSE LOGISTICS PROVIDER USING FUZZY ARAS
- Author
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Ahmad Esmaeili, Henrikas Sivilevičius, Hossein Bodaghi Khajeh Nobard, and Reza Rostamzadeh
- Subjects
reverse logistics ,Operations research ,Computer science ,02 engineering and technology ,Reverse logistics ,010501 environmental sciences ,01 natural sciences ,Fuzzy logic ,0202 electrical engineering, electronic engineering, information engineering ,MCDM ,Selection (genetic algorithm) ,0105 earth and related environmental sciences ,Sustainable development ,Fuzzy decision ,TA1001-1280 ,sustainable development ,Third party ,business.industry ,Mechanical Engineering ,FARAS ,Information technology ,Transportation engineering ,fuzzy sets ,3rdPRLPs ,Automotive Engineering ,020201 artificial intelligence & image processing ,business - Abstract
Business environment is full of ups and down and this makes companies to develop different ways of using resources. By expanding life cycle of products, these ways can be cost effective and not harmful for environment. As Reverse Logistics (RL) uses a product after end of its life, it reduces pollution, therefore it has been considered as a part of sustainable development. The core goal of current research is developing a framework by which it evaluates Third Party RL Provider (3rdPRLP) using Multi-Criteria Decision-Making (MCDM) based on Fuzzy Additive Ratio ASsessment (FARAS). Thirty-seven criteria were identified, which are classified into seven main criteria. The main criteria were ranked as follows: product lifecycle position C1, RL process function C2, organizational performance C3, organizational role of RL C4, IT system and communication C5, general company consideration C6, geographical location C7. Market coverage, destination, financial considerations, integrated system, reclaim, efficiency and quality, and growth are each group’s dominant sub-criteria. In addition, the current research helps the logistics managers to better understand the key attributes’ complex relationships in the environment of decision-making. First published online 21 January 2021
- Published
- 2021
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