Year: 2026
Type: article
Abstract: 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.
Source: Discrete Event Dynamic Systems
Authors: Daniel Sarsur, Lucas Alves, Patrícia Pena
Institution: Universidade Federal de Minas Gerais
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,290
OpenAlex ID: W7157052356