Modeling and optimization for noise-aversion and energy-awareness disassembly sequence planning problems in reverse supply chain.

Nowadays, the reverse supply chain management receives much attention because of its critical role in environmental protection and economic development. Disassembly is very important in the reverse supply chain. It aims at dismantling valuable components from end-of-life products which are then remanufactured into like-new ones after reprocessing and reassembly operations. To efficiently organize and manage the remanufacturing process from the perspective of sustainable development, this work proposes a stochastic disassembly sequence planning problem with consideration of noise pollution and energy consumption to achieve disassembly profit maximization. A chance-constrained programming model is formulated to describe it mathematically. Then, a discrete marine predators algorithm combined with a stochastic simulation approach is specially designed. By conducting simulation experiments on some real-life instances and comparing the designed approach with two popularly known methods in literature, we mainly find that the proposed model and approach can make better disassembly plan for the investigated problem with maximal profit subject to the given noise pollution and energy consumption constraints. The results demonstrate that the proposed method can efficiently and effectively handle the considered problem, which contributes to reaching the highly reliable and environmentally sustainable disassembly process.