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差分进化混合粒子群算法求解项目调度问题*
引用本文:倪霖,段超,贾春兰. 差分进化混合粒子群算法求解项目调度问题*[J]. 计算机应用研究, 2011, 28(4): 1286-1289. DOI: 10.3969/j.issn.1001-3695.2011.04.024
作者姓名:倪霖  段超  贾春兰
作者单位:重庆大学,机械传动国家重点实验室,重庆,400044
基金项目:重庆市科委自然科学基金计划资助项目 (CSTC,2008BB2173),中央高校基本科研业务费资助(Project No.CDJXS11110014 Supported by the Fundamental Research Funds for the Central Universities)
摘    要:针对求解资源受限项目调度问题(RCPSP),提出了基于差分进化(DE)的混合粒子群算法(PSODE)。通过在PSO种群和DE种群之间建立一种信息交流机制,使信息能够在两个种群中传递,以避免个体因错误的信息判断而陷入局部最优点。采用标准测试函数和具体算例进行检验,结果表明PSODE算法可以较好地解决RCPS问题。

关 键 词:差分进化混合粒子群算法;粒子群算法;差分进化算法;项目调度
收稿时间:2010-09-26
修稿时间:2010-11-03

Hybrid particle swarm optimization algorithm based on differential evolution for project scheduling problems
NI Lin,DUAN Chao,JIA Chun-lan. Hybrid particle swarm optimization algorithm based on differential evolution for project scheduling problems[J]. Application Research of Computers, 2011, 28(4): 1286-1289. DOI: 10.3969/j.issn.1001-3695.2011.04.024
Authors:NI Lin  DUAN Chao  JIA Chun-lan
Affiliation:(Dept. of Management & Information System, School of Management, Shanghai Jiao Tong University, Shanghai 200052, China)
Abstract:For resource-constrained project scheduling problem (RCPSP), the hybrid particle swarm optimization (PSODE)based on differential evolution (DE) is proposed, the new algorithm established an information exchange mechanism between the PSO population and DE population, allowing information to be transferred in two population, in order to avoid the individual to reach a local optimum for wrong information determine, and the effectiveness of the algorithm was tested by using the test function and specific examples.The results show that, PSODE algorithm can well solve RCPSP.
Keywords:hybrid particle swarm optimization algorithm based on differential evolution   particle swarm optimization   differential evolution   project scheduling  
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