A Hybrid BRKGA for Joint Scheduling Production, Transport, and Storage/Retrieval in Flexible Job Shops

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Homayouni, SM (Author) Other; Dalila B.M.M. Fontes (Author) FEP; Fontes, Fernando A C C (Author) FEUP

Conference proceedings International

Title: Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023

Pages: 211-214

2023 Genetic and Evolutionary Computation Conference Companion, GECCO 2023 Companion

Lisbon, 15 July 2023 through 19 July 2023

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Other information

Authenticus ID: P-00Y-ZQT

DOI: 10.1145/3583133.3590758

Abstract (EN): This paper addresses the joint scheduling of production operations, transport tasks, and storage/retrieval activities in flexible job shop systems where the production operations and transport tasks can be done by one of the several resources available. Jobs need to be retrieved from storage and delivered to a load/unload area, from there, they are transported to and between the machines where their operations are processed on. Once all operations of a job are processed, the job is taken back to the load/unload area and then returned to the storage cell. Therefore, the problem under study requires, concurrently, solving job routing, machine scheduling, transport allocation, vehicle scheduling, and shuttle schedule. To this end, we propose a hybrid biased random-key genetic algorithm (BRKGA) in which the mutation operator resorts to six local search heuristics. The computational experiments conducted on a set of benchmark instances show the effectiveness of the proposed mutation operator. © 2023 Copyright held by the owner/author(s).

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 3