Multiobjective scheduling algorithm for flexible manufacturing systems with Petri nets

Gonzalo Mejía, Jordi Pereira

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this work, we focus on general multi-objective scheduling problems that can be modeled using a Petri net framework. Due to their generality, Petri nets are a useful abstraction that captures multiple characteristics of real-life processes. To provide a general solution procedure for the abstraction, we propose three alternative approaches using an indirect scheme to represent the solution: (1) a genetic algorithm that combines two objectives through a weighted fitness function, (2) a non dominated sorting genetic algorithm (NSGA-II) that explicitly addresses the multi-objective nature of the problem and (3) a multi-objective local search approach that simultaneously explores multiple candidate solutions. These algorithms are tested in an extensive computational experiment showing the applicability of this general framework to obtain quality solutions.

Original languageEnglish
Pages (from-to)272-284
Number of pages13
JournalJournal of Manufacturing Systems
Volume54
DOIs
StatePublished - Jan 2020
Externally publishedYes

Keywords

  • Machine scheduling
  • Multi-objective optimization
  • Petri nets

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