Fuzzy mathematical programming approaches for reverse supply chain optimization with disassembly line balancing problem

Today, the requirement of reverse supply chain (RSC) optimization takes more attention due to environmental and competitive factors. However, increasing attention and existing uncertainty in RSC also increases the difficulties for decisions of production/distribution planning. Therefore, considering strategic and tactical decisions together under fuzziness is being essential. This paper presents a fuzzy programming approach to the integration of RSC optimization (strategic level) and disassembly line balancing (DLB) (tactical level) problems. The aim of this study is to apply fuzzy modeling to optimize a RSC that involves customers, collection/disassembly centers and plants while balancing the disassembly lines in disassembly centers, simultaneously. Two types of fuzzy mathematical programming models with different aggregation operators are used. Finally, accuracy and applicability of the model is illustrated and a comparison of fuzzy approaches is done via a hypothetical example.