Research on Flexible Job Shop Scheduling Problem Based on an Enhanced Walrus Optimization Algorithm

DOI

10.2991/978-94-6463-736-6_16How to use a DOI?

Keywords

Flexible Job Shop Scheduling Problem (FJSP); Walrus Optimization Algorithm (WWaOA); chaotic initialization; Whale Optimization Operator; crossover-mutation; makespan minimization; Brandimarte dataset; production scheduling; steel pipe industry

Abstract

This paper proposes an enhanced Walrus Optimization Algorithm (WWaOA) to address the Flexible Job Shop Scheduling Problem (FJSP) in the steel pipe industry, where complex processes and small orders cause inefficiencies. WWaOA uses chaotic initialization, a Whale Optimization Operator, and crossover-mutation to improve global and local search. Tested on the Brandimarte dataset (MK01-MK10), WWaOA outperforms ICSO, BEDA, GWO, and WaOA in minimizing makespan, offering a robust solution for production scheduling. Future research will extend WWaOA to multi-objective scheduling problems.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yunjie Shen
AU  - Ning Cui
PY  - 2025
DA  - 2025/05/22
TI  - Research on Flexible Job Shop Scheduling Problem Based on an Enhanced Walrus Optimization Algorithm
BT  - Proceedings of the 2025 4th International Conference on Engineering Management and Information Science (EMIS 2025)
PB  - Atlantis Press
SP  - 133
EP  - 138
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-736-6_16
DO  - 10.2991/978-94-6463-736-6_16
ID  - Shen2025
ER  -