A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification
Joint Authors
Wang, Yalin
Yang, Chunhua
Xu, Honglei
Gui, Weihua
Chen, Xiaofang
Caccetta, Lou
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-19
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wang, Yalin& Chen, Xiaofang& Gui, Weihua& Yang, Chunhua& Caccetta, Lou& Xu, Honglei. 2013. A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-502532
Modern Language Association (MLA)
Wang, Yalin…[et al.]. A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification. Journal of Applied Mathematics No. 2013 (2013), pp.1-15.
https://search.emarefa.net/detail/BIM-502532
American Medical Association (AMA)
Wang, Yalin& Chen, Xiaofang& Gui, Weihua& Yang, Chunhua& Caccetta, Lou& Xu, Honglei. A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-502532
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-502532