现代制造工程Issue(9)：1-11,11.DOI:10.16731/j.cnki.1671-3133.2025.09.001
基于DQN的改进NSGA-Ⅱ求解多目标柔性作业车间调度问题
Solving multi-objective flexible job shop scheduling problems with an improved NSGA-Ⅱ based on DQN
摘要
Abstract
An improved Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ)based on the Deep Q-Network(DQN)is pro-posed to solve the Multi-Objective Flexible Job shop Scheduling Problem(MO-FJSP)with the goals of minimizing makespan and energy consumption.The Markov decision process and a reward function are defined in the DQN algorithm,considering the influ-ence of selected machines on makespan and energy consumption both locally and globally.This approach enhances the quality of the initial population of the NSGA-Ⅱ.The elite retention strategy of the NSGA-Ⅱ is improved to ensure population diversity dur-ing execution and preserve high-quality individuals throughout the evolutionary process.The effectiveness of the DQN algorithm in generating initial solutions is validated by comparing its initial solutions with those generated by a greedy algorithm.Furthermore,the improved NSGA-Ⅱ based on the DQN algorithm is compared with other heuristic algorithms on standard and simulation ca-ses,demonstrating its effectiveness in solving MO-FJSP.关键词
深度Q网络算法/多目标柔性作业车间调度问题/奖励函数/非支配排序遗传算法Key words
Deep Q-Network(DQN)algorithm/multi-objective flexible job shop scheduling problem/reward function/Non-domi-nated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ)分类
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郑国梁,张朝阳,吉卫喜,于俊杰..基于DQN的改进NSGA-Ⅱ求解多目标柔性作业车间调度问题[J].现代制造工程,2025,(9):1-11,11.基金项目
国家自然科学基金青年科学基金项目(51805213) （51805213）
