Title
A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification.
Abstract
The grinding-classification is the prerequisite process for full recovery of the nonrenewable minerals with both production quality and quantity objectives concerned. Its natural formulation is a constrained multiobjective optimization problem of complex expression since the process is composed of one grinding machine and two classification machines. In this paper, a hybrid differential evolution (DE) algorithm with multi-population is proposed. Some infeasible solutions with better performance are allowed to be saved, and they participate randomly in the evolution. In order to exploit the meaningful infeasible solutions, a functionally partitioned multi-population mechanism is designed to find an optimal solution from all possible directions. Meanwhile, a simplex method for local search is inserted into the evolution process to enhance the searching strategy in the optimization process. Simulation results from the test of some benchmark problems indicate that the proposed algorithm tends to converge quickly and effectively to the Pareto frontier with better distribution. Finally, the proposed algorithm is applied to solve a multiobjective optimization model of a grinding and classification process. Based on the technique for order performance by similarity to ideal solution (TOPSIS), the satisfactory solution is obtained by using a decision-making method for multiple attributes.
Year
DOI
Venue
2013
10.1155/2013/841780
JOURNAL OF APPLIED MATHEMATICS
Field
DocType
Volume
Mathematical optimization,Simplex algorithm,Ideal solution,Multi-objective optimization,Differential evolution,Local search (optimization),TOPSIS,Grinding,Pareto principle,Mathematics
Journal
2013
Issue
ISSN
Citations 
null
1110-757X
0
PageRank 
References 
Authors
0.34
21
6
Name
Order
Citations
PageRank
YaLin Wang16419.24
Xiaofang Chen200.68
Weihua Gui357790.82
Chunhua Yang443571.63
Lou Caccetta5193.38
Honglei Xu610411.51