Multi-Objective Optimization Algorithm for Job Shop Scheduling Problem in Discrete Manufacturing Enterprise

Abstract:

Job Shop scheduling should satisfy the constraints of time, order and resource. To solve this NP-Hard problem, multi-optimization for job shop scheduling problem (JSSP) in discrete manufacturing plant is researched. Objective of JSSP in discrete manufacturing enterprise was analyzed, and production scheduling optimization model was constructed with the optimization goal of minimizing the bottleneck machines’ make-span and the total products’ tardiness; Then, Particle Swarm Optimization (PSO) algorithm was used to solve this model by the process-based encoding mode; To solve the premature convergence problem of PSO, advantages of Simulated Annealing (SA) algorithm, such as better global optimization performance, was integrated into PSO algorithm and a Hybrid PSO-SA Algorithm (HPSA) was proposed and the flowchart was presented; Then, this hybrid algorithm was applied in actual production scheduling of a discrete manufacturing enterprise. Finally, comparative analysis of HPSA/SA/PSO optimal methods and actual scheduling plan was carried out, which verify the result that the HPSA is effective and superiority.

• Periodical: Applied Mechanics and Materials (Volume 741)
• Pages: 860-864
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.741.860
• Online since: March 2015
• Authors: Li Lan Liu, Xue Wei Liu*, Sen Wang, Wei Zhou, Gai Ping Zhao
• Keywords: HPSA, Job Shop Scheduling Problem, Multi-Objective Optimization, PSO, SA

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DOI: 10.1109/icsmc.2004.1400928