Entropy-based bi-objective disassembly line balancing problem

Rigid environmental regulations, sustainable development and green manufacturing have been attracting public attention. Thus disassembly line balancing problem (DLBP), which plays a significant role in end-of-life (EOL) product recycling, is a hot research topic. Besides, the emergence of Industry 4.0 provides new paradigms for the manufacturing systems, i.e., integrating the physical and decisional aspects to support their intime communication and cooperation in manufacturing systems. Such new paradigms bring challenges for manufacturing process, including the DLBP. Especially, due to the tight links between human and manufacturing, workload balance is considered as one objective in this paper. This work studies an entropy-based bi-objective DLBP, to minimize (1) the total system cost and (2) the workload balance measured by a nonlinear entropy function. A bi-objective mixed integer nonlinear programming (MINLP) formulation is first proposed, and then the second-order Taylor series expansion approximation is applied to approximate the logarithmic objective. The ^-constraint method is further applied to obtain the Pareto front. A case study is conducted to evaluate the application of the proposed method, and some managerial insights are drawn as well.