基于细菌觅食法求解单目标约束优化问题  

Solving Single Objective Constrained Optimization Problem Based on Bacterial Foraging Method

作　　者：郭德龙 周锦程[2] 周永权 GUO De-long;ZHOU Jin-cheng;ZHOU Yong-quan(School of Mathematics and Statistics,Qiannan Normal University for Nationalities,Duyun 558000,China;Key Laboratory of Complex Systems and Intelligent Computing,Qiannan Normal University for Nationalities,Duyun 558000,China;College of Information Science and Engineering,Guangxi University for Nationalities,Nanning 530006,China)

机构地区：[1]黔南民族师范学院数学与统计学院,贵州都匀558000 [2]黔南民族师范学院复杂系统与计算智能重点实验,贵州都匀558000 [3]广西民族大学信息科学与工程学院,广西南宁530006

出　　处：《遵义师范学院学报》2024年第6期77-81,共5页Journal of Zunyi Normal University

基　　金：国家自然科学基金[61862051];贵州省科技厅联合基金项目(黔科LH[2014]7436);广西复杂系统与智能计算重点实验室开放课题项目(15CI04Y)。

摘　　要：本文应用细菌觅食算法去求带有约束的优化问题,该算法是使用罚函数法将单目标约束优化问题转化为无约束优化问题来进行求解,即利用原函数和约束函数构造一个新目标函数,再用细菌觅食算法对该新目标函数进行优化,该算法因具有群体智能算法并行搜索、易跳出局部极小值等优点,不断地寻找更优可行解,逐渐达到搜索全局最优解。数值仿真实验结果表明该方法求解带有约束优化问题是可行的,同时也验证了该算法的有效性。This paper is aimed at single objective constraint optimization problem.The problem by using the penalty function method will be constrained optimization into unconstrained optimization problems to solve.It is used the function structure,a new objective function and constraints of reoccupy bacterial foraging algorithmfor the new objective function is optimized.The algorithmhas swarm intelligence algorithmfor parallel search,the advantages of easy to jump out of local minimumvalues,etc,constantly looking for a better feasible solution,gradually to search the global optimal solution.The numerical simulation experiment results show that the method is feasible for solving constrained optimization problems,and also verify the effectiveness of the algorithm.

关 键 词：细菌觅食算法 趋向 复制 迁徙 单目标约束优化问题 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]