A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification
A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification
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DOI：
10.1155/2013/841780
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发表时间：
2013-11
期刊：
影响因子：
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通讯作者：
Yalin Wang;Xiaofang Chen;W. Gui;Chunhua Yang;L. Caccetta;Honglei Xu
中科院分区：
文献类型：
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作者：
Yalin Wang;Xiaofang Chen;W. Gui;Chunhua Yang;L. Caccetta;Honglei Xu
磨矿分级是全面回收不可再生矿物的前提过程，涉及生产质量和数量目标。由于该过程由一台磨床和两台分级机组成，因此其自然公式是一个复杂表达式的约束多目标优化问题。本文提出了一种多群体混合差分进化（DE）算法。允许保存一些性能较好的不可行解，并随机参与演化。为了利用有意义的不可行解，设计了功能分区的多群体机制以从所有可能的方向找到最优解。同时，在进化过程中插入局部搜索的单纯形方法，以增强优化过程中的搜索策略。一些基准问题的测试仿真结果表明，该算法能够快速有效地收敛到分布较好的Pareto前沿。最后，将所提出的算法应用于求解研磨和分级过程的多目标优化模型。基于理想解相似度排序技术（TOPSIS），采用多属性决策方法得到满意的解。
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.