Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40498
Title: A Diversity-controlling Adaptive Genetic Algorithm for the Vehicle Routing Problem with Time Windows
Authors: Zhu, K.Q. 
Issue Date: 2003
Source: Zhu, K.Q. (2003). A Diversity-controlling Adaptive Genetic Algorithm for the Vehicle Routing Problem with Time Windows. Proceedings of the International Conference on Tools with Artificial Intelligence : 176-183. ScholarBank@NUS Repository.
Abstract: This paper presents an adaptive genetic algorithm (GA) to solve the Vehicle Routing Problem with Time Windows (VRPTW) to near optimal solutions. The algorithm employs a unique decoding scheme with the integer strings. It also automatically adapts the crossover probability and the mutation rate to the changing population dynamics. The adaptive control maintains population diversity at user-defined levels, and therefore prevents premature convergence in search. Comparison between this algorithm and a normal fixed parameter GA clearly demonstrates the advantage of population diversity control. Our experiments with the 56 Solomon benchmark problems indicate that this algorithm is competitive and it paves way for future research on population-based adaptive genetic algorithm.
Source Title: Proceedings of the International Conference on Tools with Artificial Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/40498
ISSN: 10636730
Appears in Collections:Staff Publications

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