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利用改进的二进制狼群算法求解多维背包问题
引用本文:吴虎胜,张凤鸣,战仁军,李浩,梁晓龙.利用改进的二进制狼群算法求解多维背包问题[J].系统工程与电子技术,2015,37(5):1084-1091.
作者姓名:吴虎胜  张凤鸣  战仁军  李浩  梁晓龙
作者单位:(1. 武警工程大学装备工程学院, 陕西 西安 710086;; 2. 空军工程大学装备管理与安全工程学院, 陕西 西安 710051;; 3. 空军工程大学空管领航学院, 陕西 西安 710051)
基金项目:国家自然科学基金,陕西省自然科学基金(2013JQ8042)资助课题
摘    要:(1. Materiel Engineering College, Armed Police Force Engineering University, Xi’an 710086, China; 2. Materiel Management and Safety Engineering College, Air Force Engineering University,  Xi’an 710051, China;3. Air Traffic Control and Navigation College, Air Force  Engineering University, Xi’an 710051, China)

关 键 词:进化计算  群体智能  二进制狼群算法  组合优化  多维背包问题

Improved binary wolf pack algorithm for solving multidimensional knapsack problem
WU Hu-sheng,ZHANG Feng-ming,ZHAN Ren-jun,LI Hao,LIANG Xiao-long.Improved binary wolf pack algorithm for solving multidimensional knapsack problem[J].System Engineering and Electronics,2015,37(5):1084-1091.
Authors:WU Hu-sheng  ZHANG Feng-ming  ZHAN Ren-jun  LI Hao  LIANG Xiao-long
Institution:(1. Materiel Engineering College, Armed Police Force Engineering University, Xi’an 710086, China;; 2. Materiel Management and Safety Engineering College, Air Force Engineering University, ; Xi’an 710051, China;3. Air Traffic Control and Navigation College, Air Force ; Engineering University, Xi’an 710051, China)
Abstract:The wolf pack algorithm has been proposed based on inspiration by group survival swarm intelligence of the wolf pack, and successfully applied to complex function optimization problems and the normal 0-1 knapsack problem. To solve the multidimensional knapsack problem (MKP), a trying loading repair operator based on the MKP specific knowledge is designed to effectively repair and improve infeasible solutions. Then, traditional objective function based on large penalty parameters has been improved so as to reduce the risk of easily trapping in the local optima. Meanwhile, inspired by the reproductive rule of the wolf pack, an improved binary wolf pack algorithm (IBWPA) is proposed for solving the MKP. Simulation results based on 19 benchmark MKP instances with different scales and comparative analysis between the IBWPA and other algorithms demonstrate the effectiveness and computational robustness of the proposed algorithm.
Keywords:evolutionary computation  swarm intelligence  binary wolf pack algorithm  combinatorial optimization  multidimensional knapsack problem
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