Article Details

Abstract

For the Flexible Job Shop Scheduling Problem (FJSP) aimed at minimising maximum completion time, a Composite Multi-Strategy Enhanced Dung Beetle Optimisation Algorithm (CSTMDBO) is proposed. Firstly, during population initialisation, a dual strategy integration of Circle mapping and G-L-R is employed to enhance the quality and diversity of initial solutions. Secondly, the Golden Sine algorithm is introduced as a novel position update scheme, integrated with an adaptive t-distribution mutation strategy to balance global exploration and local exploitation. Thirdly, a Crossover Operator is employed to increase population diversity, thereby preventing premature convergence due to insufficient diversity. Finally, a greedy neighbourhood search mechanism based on critical operations is designed to enable the algorithm to conduct refined searches within local spaces. To validate the effectiveness of the improved algorithm, simulation experiments are conducted using ten standard MK test cases and one real-world application case. Comparative analysis with multiple novel algorithms demonstrates that the CSTMDBO algorithm exhibits high accuracy and robust performance when solving the FJSP problem, possessing significant engineering application value.

Keywords

improved Dung Beetle algorithm; Circle mapping; G-L-R strategy; golden sine strategy; Crossover Operator; greedy neighbourhood search

References

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Funding

General Project of Fujian Social Science Fund (FJ2022B070)

About the authors

Sun Lei (1981-), male, Han ethnicity, from Tengzhou, Shandong Province, associate professor, master's student, research direction: engineering management; Yang Zhaoyuan (2000-), male, Han ethnicity, from Yanggu, Shandong, is currently pursuing a master's degree in Industrial Engineering.