控制理论与应用2024，Vol.41Issue(3)：502-511,10.DOI:10.7641/CTA.2023.20566
基于强化学习的多技能项目调度算法
Reinforcement learning-based algorithm for multi-skill project scheduling problem
摘要
Abstract
Combinatorial explosion is a common phenomenon in multi-skill project scheduling,which leads to higher complexity in multi-skill project scheduling problem(MSPSP)than in traditional single-skill project scheduling problem.Heuristics and meta-heuristics have disadvantages in solving MSPSP.Therefore,based on the characteristics of project scheduling and the algorithmic logic of reinforcement learning,a multi-skilled project scheduling algorithm based on re-inforcement learning is designed in this paper.Firstly,the multi-skill project scheduling process is modeled as a Markov decision process(MDP).Then,a double-agent mechanism is proposed,and state integration method and action decom-position method are designed to reduce the complexity of value function learning.Finally,skills conflation algorithm is developed to reduce the time complexity of allocating resources in MSPSP.Comparative experiments between the proposed RL algorithm and heuristics show that the reinforcement learning(RL)has better performance,and experiments between the proposed RL algorithm and meta-heuristics show that the RL has higher stability and shorter running time.关键词
多技能资源/项目调度/智能算法/强化学习/并行调度Key words
multi-skill resource/project scheduling/intelligence algorithm/reinforcement learning/PSGS引用本文复制引用
胡振涛,崔南方,胡雪君,雷晓琪..基于强化学习的多技能项目调度算法[J].控制理论与应用,2024,41(3):502-511,10.基金项目
国家自然科学基金项目(71971094,71701067,72071075),湖南省自然科学基金项目(2019JJ50039)资助.Supported by the National Natural Science Foundation of China(71971094,71701067,72071075)and the Natural Science Foundation of Hunan Province(2019JJ50039). （71971094,71701067,72071075）
