A Rank Based ACO Approach for Optimal Resource Allocation and Scheduling in FMS Modeled with Labelled Petri Net

Amira Jablaoui (1) , Hichem Kmimech (2) , Layth Sliman (3, 4) , Lotfi Nabli (2)

1 Higher Institute of Computer Science and Mathematics
2 Laboratory of Automatic Control, Signal and Image Processing
3 Efrei - École d'ingénieur généraliste en informatique et technologies du numérique
4 IBISC - Informatique, BioInformatique, Systèmes Complexes

In this article, we study the NP-Hard combinatorial optimization problem of the minimum initial marking (MIM) computation in labeled Petri net (L-PN) while considering a sequence of labels to minimize the resource consumption in a flexible manufacturing system (FMS), and we propose an approach based on the ant colony optimization (ACO) precisely the extension Rank-based ACO to optimal resource allocation and scheduling in FMS. The ACO meta-heuristic is inspired by the behavior of ants in foraging based on pheromones deposit. The numerical results show that the proposed algorithm obtained much better results than previous studies.

Domains: Computer Science [cs]; Networking and Internet Architecture [cs.NI]; Computer Science [cs]; Operations Research [cs.RO]

Amira Jablaoui, Hichem Kmimech, Layth Sliman, Lotfi Nabli. A Rank Based ACO Approach for Optimal Resource Allocation and Scheduling in FMS Modeled with Labelled Petri Net. 20th International Conference on Intelligent Software Methodologies, Tools, and Techniques (SOMET 2021), Sep 2021, Cancun, Quintana Roo, Mexico. pp.688--699, ⟨10.3233/FAIA210064⟩. ⟨hal-03453230⟩