Fuzzy multi-objective linear programming approach for optimising a closed-loop supply chain network

Abstract

With the urgency of remanufacturing and environmental concerns, closed-loop supply chain (CLSC) networks have drawn the attention of researchers. Although there are many CLSC network models in the literature, most of them do not consider uncertainty in general terms. However, practical situations are often not well defined and thus cannot be described precisely in real world CLSCs. In this paper a mixed integer fuzzy mathematical model is proposed for a CLSC network which includes both forward and reverse flows with multiple periods and multiple parts. A fuzzy multi-objective model (FMOM) approach is applied to take into account the fuzziness in the capacity, objectives, demand constraints and also in the reverse rates. Computational results are presented for a number of scenarios to show and validate applicability and flexibility of the model. Results show that the proposed model presents a systematic framework which enables the logistics manager (LM) to adjust the search direction during the solution procedure to obtain a desired satisfactory solution.

Keywords:

• closed-loop supply chain
• fuzzy multi-objective programming
• mixed integer linear programming
• multi-period

Acknowledgements

The authors express their gratitude to the two anonymous reviewers for valuable comments on the paper. In carrying out this research, the authors have been supported by the Selçuk University Scientific Research Project Fund (BAP) and the Scientific and Technological Research Council of Turkey (TUBITAK) with grant number 111M040. These funds are hereby gratefully acknowledged.