Application of PES Algorithm Based on Preferred Collaborative Strategy on Integer Programming

DOI：10.13328/j.cnki.jos.005853

 作者 单位 E-mail 王占占 武汉理工大学 理学院, 湖北 武汉 430070 黄樟灿 武汉理工大学 理学院, 湖北 武汉 430070 huangzc@whut.edu.cn 侯改 武汉理工大学 理学院, 湖北 武汉 430070 唐荷花 武汉理工大学 理学院, 湖北 武汉 430070 李贺 武汉理工大学 理学院, 湖北 武汉 430070

整数规划是在科学领域和应用研究中广泛使用的一类数学模型，由于它是NP困难问题，因而求解困难.目前的求解方法是以群智能算法为主体，但这类方法一直未能很好的解决种群内部个体或者种群之间的探索与开采、竞争与协作的矛盾，基于金字塔结构的群智能演化策略（Swarm intelligence evolution strategy based on pyramid structure，简记为PES）是一种新型算法，该算法能够有效的解决上述两大矛盾.本文深入分析了PES算法的机理，构造了一种择优协作策略的模型，并将改造后的PES算法由优化函数扩展到求解整数规划问题上，最后通过探索实验以及对比实验探究了算法的收敛性、稳定性以及探寻全局最优点的性能，实验结果表明，基于择优协作策略的PES算法能够很好的求解整数规划问题.

Integer programming is a kind of mathematical model which is widely used in the field of science and applied research. Because it is a NP-hard problem, it is difficult to solve it. The solution method is to use swarm intelligence algorithm as the main body, but this kind of method has not been able to solve the spear of exploration and exploitation, competition and collaboration among individuals and populations within the population. Swarm intelligence evolution strategy based on pyramid structure is a new algorithm, which can effectively solve the above two contradictions. In this paper, the mechanism of PES algorithm is deeply analyzed, and a preferred collaborative strategy model is constructed. The improved PES algorithm is extended from the optimization function to solve the integer programming problem. Finally, Through the exploration experiment and the contrast experiment, the convergence and stability of the algorithm and the performance of the global best are explored. The experimental results show that the PES algorithm based on the optimal cooperation strategy can solve the integer programming problem well.
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