MULTI-LEVEL OPTIMIZATION OF AN AUTOMOTIVE CLOSED-LOOP SUPPLY CHAIN NETWORK WITH INTERACTIVE FUZZY PROGRAMMING APPROACHES


Creative Commons License

YILDIZBAŞI A., Calik A., PAKSOY T., Zanjirani Farahani R., Weber G.

TECHNOLOGICAL AND ECONOMIC DEVELOPMENT OF ECONOMY, vol.24, no.3, pp.1004-1028, 2018 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 3
  • Publication Date: 2018
  • Doi Number: 10.3846/20294913.2016.1253044
  • Journal Name: TECHNOLOGICAL AND ECONOMIC DEVELOPMENT OF ECONOMY
  • Journal Indexes: Social Sciences Citation Index, Scopus
  • Page Numbers: pp.1004-1028
  • Keywords: automotive industry, closed-loop supply chain, interactive fuzzy programming, multi-level programming, mixed-integer linear programming, REVERSE LOGISTICS NETWORK, MODEL, DESIGN, UNCERTAINTY, INDUSTRIES

Abstract

Closed-Loop Supply Chain (CLSC) management has attained appreciable attention over the last few years. CLSC management allows companies to manage their recovery and recycling activities of end products. Due to the latest developments in the world, producers are responsible for the collection, refurbishing, repairing and disassembly of end products at the end of their lives. This paper develops a mixed-integer CLSC model that is inspired by the automotive industry. In this model, we consider three Decision Makers (DM): Plant, Dismantler Center and Customer. Each DM has individual objectives and is responsible for only its own objective function under same constraints. In order to tackle the trade-offs among the objectives, we used four different Interactive Fuzzy Programming (IFP) approaches. The applications of the model and solution techniques are investigated in conjectural data. The paper ends with a conclusion and a call for future studies.