摘要
乘务员排班问题规模庞大并且限制因素复杂,一种公平合理的排班有利于调动乘务员的积极性。对建立的多目标排班模型进行分析和优化,并提出近似可行解以处理约束条件,基于Pareto最优的粒子群算法解决了这一问题,仿真实验表明该算法是合理的。
Crew scheduling is a large-scale problem with complexly constraints,a fair and reasonable scheduling will help to mobilize the enthusiasm of the crew. It establishes and optimizes the multi-objective scheduling model,deals constraints with approximate feasible solution,solves the problem by particle swarm optimization algorithm with the theory of Pareto. The experiment shows that the algorithm is reasonable.
出处
《微计算机信息》
2010年第3期214-216,共3页
Control & Automation
关键词
多目标优化
粒子群算法
乘务员排班模型
近似可行解
multi-objective optimization
particle swarm optimization algorithm
crew scheduling model
approximate feasible solution
