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计算机工程 ›› 2012, Vol. 38 ›› Issue (2): 21-24. doi: 10.3969/j.issn.1000-3428.2012.02.007

• 博士论文 • 上一篇    下一篇

求解学习型员工项目调度问题的HPSO算法

柳春锋 1,2,杨善林 1   

  1. (1. 合肥工业大学管理学院,合肥 230009;2. 浙江旅游职业学院,杭州 311231)
  • 收稿日期:2011-06-21 出版日期:2012-01-20 发布日期:2012-01-20
  • 作者简介:柳春锋(1977-),男,副教授、博士,主研方向:项目调度管理,智能算法;杨善林,教授、博士生导师
  • 基金资助:

    国家自然科学基金资助重点项目(71131002);国家自然科学基金资助面上项目(71071045)

Hybrid Particle Swarm Optimization Algorithm for Solving Learning Workforce Project Schedule Problem

LIU Chun-feng 1,2, YANG Shan-lin 1   

  1. (1. School of Management, Hefei University of Technology, Hefei 230009, China; 2. Tourism College of Zhejiang, Hangzhou 311231, China)
  • Received:2011-06-21 Online:2012-01-20 Published:2012-01-20

摘要: 为提高工作效率并最小化项目工期,研究学习型员工项目调度问题的求解算法。建立相应的0-1型整数非线性规划模型,提出一种混合粒子群优化算法。该算法应用基于优先规则的启发式算法生成优良的初始粒子,引入离散型算子修正经典的粒子速度和位置方程,采用改进的前向递归算法求解粒子目标函数值。数值实验结果表明,在相同运行时间内,该算法能得到比粒子群优化算法更优的解。

关键词: 项目调度, 学习型员工, 启发式算法, 混合粒子群优化算法, 优先约束

Abstract: This paper deals with the project scheduling to minimize project duration, in which learning workforce have multiple skills and increasing efficiencies. A zero-one integer nonlinear programming model is constructed, and a discrete Hybrid Particle Swarm Optimization(HPSO) algorithm is proposed. HPSO applies priority rule-based heuristic to generate good initial particle, introduces discrete operators to modify the classical particle’s velocity and position equations, and employs the revised forward recursion algorithm to compute the objective function value of particle. Numerical experiments are conducted to show that the proposed HPSO can convergence to better solution than the conventional particle swarm optimization algorithm within the same runtime.

Key words: project schedule, learning workforce, heuristic algorithm, Hybrid Particle Swarm Optimization(HPSO) algorithm, precedence constraint

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