A novel genetic algorithm for vehicle routing problem with time windows

LIU Yun-zhong

Statistic School,Xi’an University of Finance and Economics,Xi’an 710100,China



Abstract:

A novel genetic algorithm with multiple species in dynamic region is proposed,each of which occupies a dynamic region determined by the weight vector of a fuzzy adaptive Hamming neural network. Through learning and classification of genetic individuals in the evolutionary procedure,the neural network distributes multiple species into different regions of the search space. Furthermore,the neural network dynamically expands each search region or establishes new region for good offspring individuals to continuously keep the diversification of the genetic population. As a result,the premature problem inherent in genetic algorithm is alleviated and better tradeoff between the ability of exploration and exploitation can be obtained. The experimental results on the vehicle routing problem with time windows also show the good performance of the proposed genetic algorithm.

Key words:  genetic algorithm  multiple species  neural network  premature problem  vehicle routing problem with time windows

DOI：10.11916/j.issn.1005-9113.2010.03.028

Clc Number:TP18

Fund: