Affiliations: Faculty of Engineering, Department of Industrial Engineering, Dokuz Eylül University, Buca, İzmir, Turkey
Note: [] Corresponding author. Kemal Subulan, Faculty of Engineering, Department of Industrial Engineering, Dokuz Eylül University, Buca, İzmir, Turkey. Tel.: +90 2323017624; Fax: +90 2323017608; E-mail: kemal.subulan@deu.edu.tr
Abstract: Nowadays, there has been a growing interest in reverse logistics, recycling, remanufacturing and reusing due to the environmental, economical issues and legal obligations. Due to this fact, companies should take into account the remanufacturing option while preparing the medium term planning (MTP) activities instead of using traditional production planning models. There are lots of studies in the literature related to the reverse logistics (RL) and closed-loop supply chain (CLSC) network design problem which takes place in strategic planning level but a few of them handles the medium-term planning activities. Thus, a fuzzy mixed integer programming model for medium-term planning in a CLSC related to a conceptual product with remanufacturing option is developed in this paper. In the proposed model, both forward and reverse flows are included and two production alternatives are considered: either “production of new products directly in manufacturing plants” or “bringing the returned products back to ‘as new condition’ in the remanufacturing facilities”. However, real world closed-loop supply chains are surrounded with uncertainty. Thus, storage capacities, retailers' and wholesalers' demands, return rates, acceptance ratios, weekly available production/remanufacturing times, transportation upper bounds and objective function value are considered as fuzzy in the proposed model. The proposed fuzzy mathematical programming model is converted into a crisp equivalent model by utilizing several fuzzy aggregation procedures from the literature. The proposed model is applied to an illustrative case and scenario analysis is also carried out for evaluating the effects of some parameters related to the concerned collection-recovery system. Solution of the proposed model is achieved by using ILOG OPL Studio 6.3.
