Crossover and Diversity: A Study about GVR
نویسندگان
چکیده
Genetic Vehicle Representation (GVR) is a two level representational scheme, designed to deal in an effective way with all the information needed by candidate solutions, for the Vehicle Routing Problem (VRP). In this paper, we present an analysis on the influence of two crossover operators in the algorithm performance. A first study on diversity is also presented, regarding the issues of diversity measurement and possible relations to the algorithm performance. Results show that for GVR one type of crossover is more suited for solving VRP instances, and both operators may not avoid the loss of diversity. Nevertheless, solutions discovered by GVR are competitive and are the best ones found by an evolutionary algorithm.
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