Abstract
Industrial products' reuse, recovery and recycling are very important because of their environmental and economic benefits. Effective disassembly sequencing can improve recovery revenue and reduce environment impact. In this work, a stochastic dual-objective disassembly sequencing problem is establishers which includes maximizing disassembly profit and minimizing energy consumption. Two popular and classical multi-objective evolutionary algorithms, i.e., nondominated sorting genetic algorithm II and multi-objective evolutionary algorithm based on decomposition, are used to deal with this problem. By conducting simulation experiments on several numerical cases and analyzing experimental results with wellknown performance metrics, i.e., inverted generational distance and hypervolume, this work concludes that both can be used to obtain highly desired solutions.