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This paper proposes an implementation of reinforcement learning to solve the \(1\left| {ri,di} \right|\sum T{\text{i }}\) scheduling problem. An intelligent agent is trained to gain knowledge by employing Q-Learning technique. The agent is compared to a tabu search procedure to evaluate its performance. The experimental study indicates that the suggested reinforcement learning agent demonstrates strong competitiveness compared to the well-confirmed metaheuristic.

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A Reinforcement Learning Implementation for a Scheduling Problem

  • 会议论文

  • 发表日期：

    2025年

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  • Jaber El Menchoul,
  • Hatem Hadda

摘要

This paper proposes an implementation of reinforcement learning to solve the \(1\left| {ri,di} \right|\sum T{\text{i }}\) scheduling problem. An intelligent agent is trained to gain knowledge by employing Q-Learning technique. The agent is compared to a tabu search procedure to evaluate its performance. The experimental study indicates that the suggested reinforcement learning agent demonstrates strong competitiveness compared to the well-confirmed metaheuristic.