Load Distribution Optimization of Tandem Cold Mill Based on Quantum Chaos Multi-Objective Evolutionary Algorithm

Abstract:

A novel quantum multi-objective evolutionary algorithm is proposed that combine the quantum computing with multi-objective evolutionary algorithm, and the quantum chromosomes is updated with the chaos in order to enhance the optimization capability of the quantum population. To verify the performance of the proposed algorithm, the functions ZDT1 and ZDT2 are optimized by the proposed algorithm and NSGA-II. The results show that the quantum chaos multi-objective evolutionary algorithm has the more powerful capability. The new proposed algorithm is applied to the load distribution optimization of tandem cold mill, and the two-objective function modal is built based on the minimum energy consumption and rolling force equilibrium. Optimizing the modal with the new algorithm, the empirical data and method of weighting, the result of quantum chaos multi-objective evolutionary algorithm is more reasonable. Therefore, the quantum chaos multi-objective evolutionary algorithm is a practicable intelligent optimization method for the load distribution optimization of tandem cold mill.

• Periodical: Advanced Materials Research (Volumes 774-776)
• Pages: 1208-1215
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.774-776.1208
• Online since: September 2013
• Authors: Wan Lu Jiang, Sheng Zhang, Jin Na He
• Keywords: Chaos, Load Distribution, Multi-Objective Optimization (MOP), Quantum Computing, Tandem Cold Mill

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