Application of the hybrid multi-objective particle swarm optimization algorithm in load distribution of hot finishing mills
HUANG Pei-qiu
LIU Jian-chang
TAN Shu-bin
WANG Hong-hai
Abstract：Through the analysis of the process of load distribution of hot finishing mills, a multi-objective optimiza-tion model is established with load balancing, good strip shape and minimum power. In order to improve the diversity and convergence performance of Pareto optimal solutions obtained by multi-objective optimization algorithm, a hybrid multi-objective particle swarm optimization algorithm (HMOPSO) is proposed. HMOPSO obtains Pareto front based on the Pareto dominance which can promote population convergence towards Pareto front, and uses the decomposition to maintain external archive by the method of objective space being normalized based on the nadir point of Pareto front and population being partitioned, which can improve the distribution performance of population. Simulation results show that the convergence and distribution performance of the Pareto optimal solutions obtained by HMOPSO are competitive with respect to MOPSO and dMOPSO;the fuzzy multi-attribute decision-making method is adopted to select a Pareto optimal solution from Pareto optimal solution set, and the results show that the solution can get a more reasonable rolling plan compared with the empirical load distribution method.
Keywords：load distribution of hot finishing millsmulti-objective optimizationparticle swarm optimization algorithmPareto dominancedecomposition
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 93-100 )