A MULTI-OBJECTIVE-BASED VEHICLE ASSIGNMENT MODEL FOR CONSTRAINTS HANDLING IN COMPUTATIONAL INTELLIGENCE ALGORITHMS
The vehicle transportation problem, studied in the paper, is a complex assignment problem which requires allocating vehicles to destinations to complete various jobs. The challenges is not only the potential dimensional explosion when the scenarios become more complicated and the size of problems increases, but also the constraints handling which is a specific characteristic compared with other scheduling or assignment problems. In this paper, a “Constraint-First-Objective-Next model is proposed to handle constraints as an additional objective. Thus it can be easily adapted by computational intelligence algorithms. The proposed model can effectively deal with various constraints, including the constraints expressed by nature language, and is flexible and effective enough to be combined with kinds of computation intelligence algorithms which is demonstrated by numerical experiments.
assignment problem multi-objective constraint optimization particle swarm optimizer genetic algorithms differential evolution
Feng PAN Jie CHEN Xu-yan TU Tao CAI
Department of Automatic Control,Beijing Institute of Technology,Beijing,100081,China
国际会议
2008年拟人系统国际会议(2008 International Conference on Humanized Systems )(ICHS’08)
北京
英文
2008-10-18（万方平台首次上网日期，不代表论文的发表时间）