Multi-Objective Artificial Bee Colony Algorithm for Balancing Partial Disassembly Line
Disassembly lines are widely utilized to disassemble end-of-life products.Most of the researches focus on the complete disassembly of discarded products,whereas there is a lack of research on disassemb-ling profit and carbon emission saving.For partial disassembly line balancing,this study formulates a multi-objective mathematical model to optimize profit,carbon emission saving and line balance.In order to a-chieve the high-quality solution of this problem,an improved multi-objective artificial bee colony algorithm is developed.The algorithm utilizes the two-layer encoding of task permutation vector and the number of disassembled parts,and develops the two-layer decoding to deal with the precedence constraint and the cy-cle time constrain respectively.In this algorithm,employed bee phase utilizes the neighborhood operation and onlooker phase employs the crossover operator to achieve diverse population,and the scout phase se-lects a solution from the permanent Pareto front to replace the abandoned individual to obtain a new high-quality solution.In order to test the performance of the improved algorithm,the proposed algorithm is com-pared with the original multi-objective artificial bee colony algorithm,multi-objective simulated annealing algorithm,and fast nondominated genetic algorithm.The test results demonstrates that the improved strategy effectively improves the performance of the artificial bee colony algorithm,and the improved artificial bee colony algorithm outperforms the compared methods,which can realize the high-quality solutions for the multi-objective disassembly line balancing problems.
partial disassembly line balancingcarbon emissionsmulti-objective optimizationmulti-objec-tive artificial bee colony algorithm
万方数据
维普
