基于改进灰狼算法的回收与拆卸联合调度问题研究

针对闭环供应链回收拆卸环节,文章进行废品回收再利用系统中回收与拆卸两阶段联合调度问题的研究,结合实际运行情况并考虑加工过程中的仓库容量限制,以最小化回收与拆卸的总成本、最小化完工时间为目标,提出一种改进的多目标灰狼算法。针对联合调度的两阶段调度过程,设计基于工序、机器、运输的三层编码策略;采用Tent映射进行种群的初始化,以保证种群的多样性;采用非线性调整收敛因子策略提升搜索能力和收敛速度;引入粒子群优化思想来改善灰狼算法的个体位置更新过程;以模拟退火策略决定最终个体位置的更新结果。仿真实验以及与其他相关领域算法的对比结果验证了文章所提算法在路径调度和拆卸联合调度问题优化上的适用性和优越性。

Focusing on the recycling and disassembly link of the closed-loop supply chain, this paper studies the joint scheduling problem of recycling and disassembly in the waste recycling and reuse system. Combined with the actual operation situation, considering the warehouse capacity limit during the processing process, and aiming to minimize the total cost of recycling and disassembly and minimize the completion time, an improved multi-objective grey wolf algorithm is proposed. For the two-stage scheduling process of joint scheduling, a three-layer coding strategy based on processes, machines, and transportation is designed; the Tent map is used to initialize the population to ensure the diversity of the population; a nonlinear adjustment convergence factor strategy is used to improve search capabilities and convergence speed; the idea of particle swarm optimization is introduced to improve the individual position update process of the grey wolf algorithm; the simulated annealing strategy is used to determine the final individual position update result. Finally, experimental simulations and comparisons with algorithms in other related fields are used to verify the applicability and superiority of the proposed algorithm in optimizing path scheduling and disassembly joint scheduling problems.