【精选】（吐血整理）118篇强化学习求解车间调度文章（英文）大全 |
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【精选】（吐血整理）118篇强化学习求解车间调度文章（英文）大全
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获取更多资讯，赶快关注上面的公众号吧！ 在读博期间，由于课题也是与深度强化学习求解车间调度问题相关，所以一直关注这个领域的文章，我的博士论文第二章也做了详细的综述。最近也有不少粉丝在寻求强化学习求解车间调度的文章，所以就想着怎么给粉丝传递这些文章。这个领域发展速度实在太快，通过发表综述论文这种比较慢的方式着实难以满足粉丝的需求，所以还是希望通过公众号文章的形式分享给大家，包括endnote参考文献格式和原文，希望对大家有所帮助，吐血整理实属不易，多多转发，不胜感激。关注公众号，后台回复“综述”获取参考文献。 从1995年最早将强化学习用于车间调度问题后，在随后的几年里，强化学习一直不温不火，最主要的原因是一般的强化学习无法解决状态空间爆炸的问题，直到2018年深度强化学习开始进军调度领域，并在随后的几年里爆发式增长，在2022年上半年还未结束的情况下，已有11篇甚至更多的文章发表，可见这个方向的火热。一方面深度强化学习确实利用深度学习领域技术实现了未知状态下行为的预测，另一方面车间调度一直是悬而未决的经典问题，也是检验包括深度强化学习在内的各种算法的测试床。
下面是从最近几年开始整理的文章，供大家参考。 序号年份期刊or会议文章12022SustainabilityDynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization22022MachinesDeep Reinforcement Learning for Distributed Flow Shop Scheduling with Flexible Maintenance32022Computers & Operations ResearchDigital twin-enabled dynamic scheduling with preventive maintenance using a double-layer Q-learning algorithm42022Journal of Intelligent ManufacturingOn reliability of reinforcement learning based production scheduling systems: a comparative survey52022International Journal of Production ResearchDeep reinforcement learning for dynamic scheduling of a flexible job shop62022Robotics and Computer-Integrated ManufacturingReal-time data-driven dynamic scheduling for flexible job shop with insufficient transportation resources using hybrid deep Q network72022Expert Systems with ApplicationsDeep reinforcement learning based scheduling within production plan in semiconductor fabrication82022Journal of Manufacturing SystemsMulti-objective optimization of the textile manufacturing process using deep-Q-network based multi-agent reinforcement learning92022Autonomous Agents and Multi-Agent SystemsA practical guide to multi-objective reinforcement learning and planning102022Applied SciencesMinimizing the Late Work of the Flow Shop Scheduling Problem with a Deep Reinforcement Learning Based Approach112022ProcessesDeep Reinforcement Learning for Dynamic Flexible Job Shop Scheduling with Random Job Arrival122021Ieee AccessReinforcement Learning With Composite Rewards for Production Scheduling in a Smart Factory132021Computers & Industrial EngineeringA cooperative water wave optimization algorithm with reinforcement learning for the distributed assembly no-idle flowshop scheduling problem142021Sensors (Basel)Intelligent Decision-Making of Scheduling for Dynamic Permutation Flowshop via Deep Reinforcement Learning152021Journal of Manufacturing SystemsA fast decision-making method for process planning with dynamic machining resources via deep reinforcement learning1620212021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA)Smart Scheduling for Flexible and Hybrid Production with Multi-Agent Deep Reinforcement Learning172021Computer NetworksDynamic job-shop scheduling in smart manufacturing using deep reinforcement learning182021Complex System Modeling SimulationA Review of Reinforcement Learning Based Intelligent Optimization for Manufacturing Scheduling19202117th IFAC Symposium on Information Control Problems in Manufacturing (INCOM)Enabling adaptable Industry 4.0 automation with a modular deep reinforcement learning framework20202123rd International Conference on Enterprise Information Systems (ICEIS)Global Reward Design for Cooperative Agents to Achieve Flexible Production Control under Real-time Constraints212021International Journal of Production ResearchLearning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning222021International Journal of Production ResearchDeep reinforcement learning in production systems: a systematic literature review232021Ieee Transactions on Emerging Topics in Computational IntelligenceDeep Reinforcement Learning Based Optimization Algorithm for Permutation Flow-Shop Scheduling242021Neural Computing and ApplicationsA Prioritized objective actor-critic method for deep reinforcement learning252021Journal of Intelligent ManufacturingModular production control using deep reinforcement learning: proximal policy optimization26202117th IFAC Symposium on Information Control Problems in Manufacturing (INCOM)A Deep Reinforcement Learning approach for the throughput control of a Flow-Shop production system272021Ieee Transactions on Automation Science and EngineeringReal-Time Scheduling for Dynamic Partial-No-Wait Multiobjective Flexible Job Shop by Deep Reinforcement Learning282021Computers & Industrial EngineeringDynamic multi-objective scheduling for flexible job shop by deep reinforcement learning292021Mathematical Problems in EngineeringA Kind of Reinforcement Learning to Improve Genetic Algorithm for Multiagent Task Scheduling302021International Journal of Production ResearchReinforcement learning for robotic flow shop scheduling with processing time variations312021Procedia CIRPDynamic scheduling in a job-shop production system with reinforcement learning322021Journal of Manufacturing SystemsMulti-objective optimization of the textile manufacturing process using deep-Q-network based multi-agent reinforcement learning332021International Journal of Simulation ModellingA Deep Reinforcement Learning Based Solution for Flexible Job Shop Scheduling Problem3420213rd International Conference on Industry 4.0 and Smart Manufacturing (ISM)Integration of the A2C Algorithm for Production Scheduling in a Two-Stage Hybrid Flow Shop Environment352021Applied Sciences-BaselIntelligent Scheduling with Reinforcement Learning362021Computers & Industrial EngineeringAgent-based approach integrating deep reinforcement learning and hybrid genetic algorithm for dynamic scheduling for Industry 3.5 smart production372021International Journal of Production ResearchEnd-to-end on-line rescheduling from Gantt chart images using deep reinforcement learning382020Proceedings of 2020 Ieee 9th Data Driven Control and Learning Systems ConferenceA Deep Reinforcement Learning Approach to the Flexible Flowshop Scheduling Problem with Makespan Minimization392020Procedia CirpDeep reinforcement learning-based dynamic scheduling in smart manufacturing402020Advances in Neural Information Processing SystemsLearning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning412020International Journal of Production ResearchAdaptive scheduling for assembly job shop with uncertain assembly times based on dual Q-learning422020AAS/AIAA Astrodynamics Specialist ConferenceUsing multi-objective deep reinforcement learning to uncover a pareto front in multi-body trajectory design432020International Journal of Production ResearchIntelligent scheduling of discrete automated production line via deep reinforcement learning442020Icaart: Proceedings of the 12th International Conference on Agents and Artificial Intelligence, Vol 2Production Scheduling based on Deep Reinforcement Learning using Graph Convolutional Neural Network452020International Journal of Simulation ModellingA NOVEL SOLUTION TO JSPS BASED ON LONG SHORT-TERM MEMORY AND POLICY GRADIENT ALGORITHM462020Ieee Transactions on Automation Science and EngineeringA Reinforcement Learning Approach to Robust Scheduling of Semiconductor Manufacturing Facilities4720202020 Prognostics and Health Management Conference (PHM-Besanon)Solving Permutation Flowshop Problem with Deep Reinforcement Learning482020Applied Soft ComputingDynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning492020IEEE AccessActor-Critic Deep Reinforcement Learning for Solving Job Shop Scheduling Problems5020202020 IEEE 16th International Conference on Automation Science and Engineering (CASE)Adaptive Scheduling for Smart Shop Floor Based on Deep Q-Network5120202020 Ieee 32nd International Conference on Tools with Artificial IntelligenceSolving Open Shop Scheduling Problem via Graph Attention Neural Network5220202020 Winter Simulation Conference (WSC)Integration of Deep Reinforcement Learning and Discrete-Event Simulation for Real-Time Scheduling of a Flexible Job Shop Production532020Journal of Manufacturing SystemsPetri-net-based dynamic scheduling of flexible manufacturing system via deep reinforcement learning with graph convolutional network542020Computers & Industrial EngineeringDeep reinforcement learning based AGVs real-time scheduling with mixed rule for flexible shop floor in industry 4.0552020IEEE AccessResearch on Adaptive Job Shop Scheduling Problems Based on Dueling Double DQN562020Computers & Industrial EngineeringA self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem572019European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)Manufacturing Dispatching Using Reinforcement and Transfer Learning582019IEEE AccessMulti-Objective Workflow Scheduling With Deep-Q-Network-Based Multi-Agent Reinforcement Learning592019Ifac PapersonlinePractical Reinforcement Learning - Experiences in Lot Scheduling Application602019Ifac PapersonlineClosed-loop Rescheduling using Deep Reinforcement Learning612019Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural ComputationA Multi-objective Reinforcement Learning Algorithm for JSSP622019Ieee Transactions on Industrial InformaticsSmart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network632019Procedia CIRPAutonomous order dispatching in the semiconductor industry using reinforcement learning642019Investigacion OperacionalOptimization of heavily constrained hybrid-flexible flowshop problems using a multi-agent reinforcement learning approach65201913th INTERNATIONAL CONFERENCE on OPERATIONS RESEARCH (ICOR 2018)AN IMPROVEMENT OF REINFORCEMENT LEARNING APPROACH TO PERMUTATIONAL FLOW SHOP SCHEDULING PROBLEM6620192019 Second International Conference on Artificial Intelligence for Industries (AI4I)Multi-agent reinforcement learning for job shop scheduling in flexible manufacturing systems6720182018 29th annual SEMI advanced semiconductor manufacturing conference (ASMC)Deep reinforcement learning for semiconductor production scheduling682019Procedia CIRPOptimization of global production scheduling with deep reinforcement learning692018Journal of Intelligent ManufacturingAdaptive job shop scheduling strategy based on weighted Q-learning algorithm702018CIRP AnnalsReinforcement learning for adaptive order dispatching in the semiconductor industry712018Computers & Industrial EngineeringReal-time scheduling for a smart factory using a reinforcement learning approach7220182018 Ieee Biennial Congress of ArgentinaAutomatic Generation of Rescheduling Knowledge in Socio-technical Manufacturing Systems using Deep Reinforcement Learning732018IEEE AccessGantry Work Cell Scheduling through Reinforcement Learning with Knowledge-guided Reward Setting742017Computers & Industrial EngineeringA reinforcement learning approach to parameter estimation in dynamic job shop scheduling752017Revista Cubana de Ciencias InformáticasAdapting a Reinforcement Learning Approach for the Flow Shop Environment with sequence-dependent setup time762017Applied SciencesManufacturing Scheduling Using Colored Petri Nets and Reinforcement Learning772017IFAC-PapersOnLineA distributed approach solving partially flexible job-shop scheduling problem with a Q-learning effect782016Journal of Intelligent ManufacturingAn interoperable adaptive scheduling strategy for knowledgeable manufacturing based on SMGWQ-learning7920162016 Ieee 21st International Conference on Emerging Technologies and Factory AutomationLearning Adaptive Dispatching Rules for a Manufacturing Process System by Using Reinforcement Learning Approach802016Procedia CIRPOptimized Adaptive Scheduling of a Manufacturing Process System with Multi-skill Workforce and Multiple Machine Types: An Ontology-based, Multi-agent Reinforcement Learning Approach812016International Journal of Production ResearchCollaborative reinforcement learning for a two-robot job transfer flow-shop scheduling problem822015Proceedings of 2015 Ieee 20th Conference on Emerging Technologies & Factory AutomationA Centralized Reinforcement Learning Approach for Proactive Scheduling in Manufacturing832015Service Orientation in Holonic and Multi-agent ManufacturingA Model for Manufacturing Scheduling Optimization Through Learning Intelligent Products842014Iowa State UniversityPolicy based reinforcement learning approach Of Jobshop scheduling with high level deadlock detection852013Asia-Pacific Journal of Operational ResearchFlow shop scheduling with reinforcement learning862012Computers & Operations ResearchMinimizing mean weighted tardiness in unrelated parallel machine scheduling with reinforcement learning872012International Journal of Production ResearchIntelligent dynamic control of stochastic economic lot scheduling by agent-based reinforcement learning882012Expert Systems with ApplicationsSmartGantt – An intelligent system for real time rescheduling based on relational reinforcement learning892012Journal of Intelligent ManufacturingDynamic scheduling for multi-site companies: a decisional approach based on reinforcement multi-agent learning902011European Journal of Operational ResearchSemiconductor final test scheduling with Sarsa(λ,k) algorithm9120112011 IEEE International Summer Conference of Asia Pacific Business Innovation and Technology ManagementReinforcement learning combined with radial basis function neural network to solve Job-Shop scheduling problem922011International Conference on Production ResearchFlow-Shop Robotic Scheduling Problem with Collaborative Reinforcement Learning932011Learning and Intelligent OptimizationA Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem9420102010 IEEE International Conference on Industrial Engineering and Engineering ManagementReinforcement learning based scheduling in semiconductor final testing9520102010 IEEE International Conference on Automation and LogisticsRule driven multi objective dynamic scheduling by data envelopment analysis and reinforcement learning962009International Journal of Advanced Manufacturing TechnologyAn adaptive approach to dynamic scheduling in knowledgeable manufacturing cell9720092009 Fifth International Conference on Natural ComputationMulti-agent Co-evolutionary Scheduling Approach Based on Genetic Reinforcement Learning982009Universität OsnabrückMulti-Agent Reinforcement Learning Approaches for Distributed Job-Shop Scheduling Problems992007International Journal of Advanced Manufacturing TechnologyDynamic parallel machine scheduling with mean weighted tardiness objective by Q-Learning10020072007 IEEE Symposium on Computational Intelligence in SchedulingScaling Adaptive Agent-Based Reactive Job-Shop Scheduling to Large-Scale Problems1012007International Journal of Information Technology and Intelligent ComputingAdaptive Reactive Job-Shop Scheduling with Reinforcement Learning Agents1022006Advanced Engineering InformaticsReinforcement learning in a distributed market-based production control system1032005Engineering Applications of Artificial IntelligenceApplication of reinforcement learning for agent-based production scheduling1042005Simulation Modelling Practice and TheoryA multi-agent reinforcement learning approach to obtaining dynamic control policies for stochastic lot scheduling problem1052005Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference onDynamic single machine scheduling using Q-learning agent1062005IEEE Transactions on Automation Science and EngineeringRelative value function approximation for the capacitated re-entrant line scheduling problem1072005Multi-Agent Systems and Applications Iv, ProceedingsStochastic reactive production scheduling by multi-agent based asynchronous approximate dynamic programming10820042004 Ieee Conference on Robotics, Automation and Mechatronics, Vols 1 and 2Composite rules selection using reinforcement learning for dynamic job-shop scheduling1092004Robotics and Computer-Integrated ManufacturingLearning policies for single machine job dispatching1102004Applied IntelligenceDistributed Reinforcement Learning Control for Batch Sequencing and Sizing in Just-In-Time Manufacturing Systems1112003Mississippi State University, M1 - Degree of Doctor of PhilosophyApplication of reinforcement learning to multi-agent production scheduling1122003Production Systems and Information EngineeringFlow-shop scheduling based on reinforcement learning algorithm11320012001 International Conferences on Info-Tech and Info-Net. Proceedings (Cat. No.01EX479)Reinforcement learning approach to re-entrant manufacturing system scheduling1142000International Transactions in Operational ResearchLearning scheduling control knowledge through reinforcements1152000Robotics and Autonomous SystemsDynamic job-shop scheduling using reinforcement learning agents1161999IEEE SMC’99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028)An application of reinforcement learning to manufacturing scheduling problems1171999Proceedings of the Sixteenth International Joint Conference on Artificial IntelligenceA Neural Reinforcement Learning Approach to Learn Local Dispatching Policies in Production Scheduling1181995Proc. of 14th Int. Joint Conf. on Artificial IntelligenceA Reinforcement Learning Approach to Job-Shop Schedulling |
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