Scholarlink

<p>This work integrates Markov Decision Process (MDP) framework with Supervisory Control Theory (SCT) to address production planning challenges, especially minimizing makespan. By leveraging MDP’s sequential decision-making framework and SCT’s constraint based framework, the approach ensures online decision-making in dynamic industrial environments. The feasibility of this integration is demonstrated through the formalization of a mapping between the two approaches. The results demonstrate that the proposed approach efficiently solves the tested problems, achieving makespan values close to the reference solution but with significantly lower processing times in most cases.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Task scheduling using Markov decision process over supervisory control theory

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月28日

查看全文
  • Daniel Sarsur,
  • Lucas Alves,
  • Patrícia Pena

摘要

This work integrates Markov Decision Process (MDP) framework with Supervisory Control Theory (SCT) to address production planning challenges, especially minimizing makespan. By leveraging MDP’s sequential decision-making framework and SCT’s constraint based framework, the approach ensures online decision-making in dynamic industrial environments. The feasibility of this integration is demonstrated through the formalization of a mapping between the two approaches. The results demonstrate that the proposed approach efficiently solves the tested problems, achieving makespan values close to the reference solution but with significantly lower processing times in most cases.