Multi-agent reinforcement learning-aided evolutionary algorithm for a many-objective distributed hybrid flow shop scheduling problem

doi:10.1016/j.swevo.2025.101991

Multi-agent reinforcement learning-aided evolutionary algorithm for a many-objective distributed hybrid flow shop scheduling problem

2025-06-28

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DOI：10.1016/j.swevo.2025.101991

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• A variant of distributed hybrid flow shop scheduling problem is studied. • Time-of-use electricity tariffs, delivery dates, and worker costs are considered. • Multi-agent reinforcement learning is integrated into an evolutionary framework. • Intelligent local search is conducted based on multi-agent group decision-making. • Comprehensive experiments verify the superior performance of our method.

Multi-agent reinforcement learning-aided evolutionary algorithm for a many-objective distributed hybrid flow shop scheduling problem

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