A reinforcement learning-based multi-agent framework applied for solving routing and scheduling problems
Expert Systems with Applications(2019)
摘要
•Multi-agent framework for optimization using metaheuristics.•Agents modify their actions using concepts of Reinforcement Learning.•Learning ability of the agents directly influences the quality of solutions.•Framework validated using Vehicle Routing Problem with Time-Windows (VRPTW) and Unrelated Parallel Machine Scheduling Problem with Sequence-Dependent Setup Times (UPMSP-ST).
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关键词
Multi-agent framework for optimization,Reinforcement learning,Metaheuristics,Multi-agent systems,Vehicle routing problem with time window,Unrelated parallel machine scheduling problem
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