基于动态多目标粒子群优化算法的资源受限研发项目进度  

The Resource-constrained R&G Project Scheduling Problem Based on Dynamic Multi-object Particle Swarm Optimization Algorithm

作　　者：曲红[1] 吴娟[1] 

机构地区：[1]湖南大学工商管理学院

出　　处：《系统工程》2007年第9期98-102,共5页Systems Engineering

摘　　要：资源与进度优化调度已成为企业研发项目成功的关键。引入粒子群算法来解决这一问题,将普通粒子群多目标算法进行了改进,提出动态的多目标粒子群算法,通过采用VC++编程语言对模型及其求解算法进行案例仿真,证实了模型及算法的有效性与优越性。Resource and scheduling optimization in enterprise has become the key to the R＆G project＇s success. PSO introduced to solve this problem, the article proposed dynamic particle swarm multiple objective algorithm through improving original particle swarm multiple objective algorithms. The simulation on the model and algorithm proved the validity and sutmriority of the model and algorithm by using VC＋＋.

关 键 词：资源受限 研发项目进度问题 多日标模型 动态多日标粒子群优化算法 

分 类 号：F270[经济管理—企业管理]