计算机与现代化Issue(6)：83-87,5.DOI:10.3969/j.issn.1006-2475.2011.06.024
求解多维背包问题的贪心粒子群算法
Greedy Particle Swarm Algorithms for Multidimensional Knapsack Problems
摘要
Abstract
Two new greedy transformations and the inspired algorithms are proposed to solve multi-dimensional knapsack problems ( MKP01 ) with weight and volume constraints. Convex combination and infinite norm of the ratio vectors of performance to weight and pefformance to volume are computed and two integrative "performance-price ratio" vectors are obtained. Two greedy PS0s variants (wPSO: weighted PSO, infPSO: infinite norm PSO) are presented for MKP01 based on the integrative "performanceprice ratio". The standard PSO, hybrid wPSO and infPS0 are applied to solve various scales of MKP instances. Numerical experiments illustrate that wPS0 and infPS0 not only outperform PSO greatly, but also show excellent and steady searching abilities and encouraging efficiency to locate the optimal solutions.关键词
多维背包问题/粒子群算法/贪心变换/混合性价比Key words
multidimensional knapsack problem/ particle swarm optimization/ greedy transformation/ integrative performanceprice ratio分类
信息技术与安全科学引用本文复制引用
郝俊玲..求解多维背包问题的贪心粒子群算法[J].计算机与现代化,2011,(6):83-87,5.基金项目
对外经济贸易大学校级科研课题资助项目(10QNGLX02) （10QNGLX02）
