Computer Engineering and Applications ›› 2016, Vol. 52 ›› Issue (7): 253-258.

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Study on multi-resource constraints vehicle scheduling problem based on improved genetic algorithm

ZHANG Yu, JIA Suimin   

  1. School of Information Science and Technology, Zhengzhou Normal University, Zhengzhou 450044, China
  • Online:2016-04-01 Published:2016-04-19

多资源约束的车辆调度问题的改进遗传算法

张  玉,贾遂民   

  1. 郑州师范学院 信息科学与技术学院,郑州 450044

Abstract: With the development of world economy, logistics industry has to meet the requirements increasingly, vehicle scheduling management is an important part of logistics system. How to implement the vehicle in the case of multiple resource constraints of reasonable scheduling is the key problem to promote the prosperity and development of modern logistics industry. Therefore, through the research of logistics distribution vehicle scheduling needs, in view of the traditional genetic algorithm, hindered the development of vehicle scheduling and improve to slow the rapid development of logistics industry shortcomings, a genetic algorithm which is improved, efficient, available for the normal vehicle scheduling problem is proposed. By demonstrating example, it shows that the algorithm is feasible and effective.

Key words: multiple resource constraints, vehicle scheduling problem, improved genetic algorithm

摘要: 随着世界经济的发展,物流产业中需要满足的需求越来越多,车辆管理调度是物流系统中一个重要环节。如何在多资源约束的情况下实现车辆的合理的调度是促进现代物流业繁荣和发展的关键问题,因此,通过研究物流配送中的车辆调度需求,针对传统的遗传算法阻碍了车辆调度的发展和改进,减缓物流业快速发展的缺点,提出一种改进的、有效的,对一般车辆调度问题具有一定适用性的遗传算法。通过实例论证表明该算法具有可行性和高效性。

关键词: 多资源约束条件, 车辆调度问题, 改进遗传算法