摘要
广义指派问题是典型的NP-hard组合优化问题。对一类广义指派问题进行了建模,提出了一种基于连续空间的改进离散粒子群优化算法以求解该模型。算法针对问题设计了特定的粒子编码方案,引入了局部搜索以改进算法性能。数值仿真表明了所提离散粒子群优化算法求解广义指派问题的可行性。
Generalized assignment problem is a typical NP-hard problem in combinatorial optimization. Model for a class of generalized assignment problem is build up, and an improved discrete particle swarm optimization algorithm based on continuous space is proposed to solve this model. The algorithm designs a specific particle coding scheme based on the problem, introduces local search to increase performance. The simulation shows that the proposed algorithm is feasible in solving generalized assignment problem.
出处
《科技通报》
北大核心
2013年第8期130-132,共3页
Bulletin of Science and Technology
基金
军内科研资助项目
关键词
广义指派问题
粒子群优化算法
粒子编码
局部搜索
generalized assignment problem
particle swarm optimization algorithm
particle coding
local search
