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This paper particularly describes a MultiObjective Chromosome-length-variant Genetic Algorithm (MCGA) as an algorithm for finding the most beautiful route of map navigation, compared to the conventional navigation which can only obtain the shortest route. The critical task to this problem is how to deal with multiobjective optimization and the length-variant chromosome. We proposed a dual stage linear polymeric fitness function which can well balance the multi-object and optimize the convergence effect. Cross and mutate operators are modified to a new set of insert, delete and mutate operators which can potentially process all possible route in navigation. Additionally, a sort operator is added to the algorithm to enhance convergence rate. Illustrative experiment results of how the MCGA obtains the most beautiful route from Shanghai to Chengdu are presented. The results also show that users have the ability to choose any candidate route primarily depending on their favor. Keywords-the most beautiful route, GA, multi-object, length-variant chromosome

Obtaining the Most Beautiful Route of Map Navigation Based on Genetic Algorithms