求解学习型员工项目调度问题的HPSO算法

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

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。

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.