Current Situation and Development of Advanced Planning and Scheduling System Based on Group Optimization Algorithm in Discrete Industry

Authors

  • Miao Wang
  • Yuhua Huang
  • Jindong Zhang

DOI:

https://doi.org/10.54097/hset.v23i.3270

Keywords:

APS, PSO, Group optimization algorithm, Advanced planning and scheduling.

Abstract

Discrete industry, especially job shop scheduling, has always been the key industry of Advanced Planning and Scheduling system (APS) system application. Based on Particle Swarm optimization (PSO), this paper introduces the Group swarm optimization algorithm, expounds the relevant theory and development status of APS, introduces the application of Particle Swarm optimization and Artificial Bee Colony optimization algorithm in APS system, and analyzes the performance and efficiency of the two algorithms. Finally, it predicts the future development trend of APS: the core algorithm will adopt a variety of hybrid algorithms, and the data flow will be combined with ERP / MES system.

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References

Alkhateeb, Faisal, Abed-alguni, Bilal H. Discrete hybrid cuckoo search and simulated annealing algorithm for solving the job shop scheduling problem [J]. JOURNAL OF SUPERCOMPUTING, 2022(03), 78(4), pp.4799-4826.

Gao, Kaizhou, Cao Zhiguang. A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems [N]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2019(07), 6(4), pp.904-916.

Abdel-Kader, Rehab F. An improved PSO algorithm with genetic and neighborhood-based diversity operators for the job shop scheduling problem [J]. APPLIED ARTIFICIAL INTELLIGENCE, 2018, 32(5), pp.433-462.

Singh M.R., Singh M, Mahapatra S.S., et al. Particle swarm optimization algorithm embedded with maximum deviation theory for solving multi-objective flexible job shop scheduling problem [J]. Int. J. Adv. Manuf. Technol, 2016, 85(9–12), pp. 2353-2366.

Warisa W, Voratas K. A pareto-based differential evolution algorithm for multi-objective job shop scheduling problems [J]. Proceedings of the Institute of Industrial Engineers Asian Conference 2013, Springer Singapore, pp. 1117-1125.

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Published

03-12-2022

How to Cite

Wang, M., Huang, Y., & Zhang, J. (2022). Current Situation and Development of Advanced Planning and Scheduling System Based on Group Optimization Algorithm in Discrete Industry. Highlights in Science, Engineering and Technology, 23, 215-220. https://doi.org/10.54097/hset.v23i.3270