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A Genetic Algorithm for Optimizing Parameters for Ant Colony Optimization Solving Capacitated Vehicle Routing Problems

ACM International Conference Proceeding Series (2020) 52-58
DOI: 10.1145/3396474.3396489
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Abstract

This paper discusses the combined application of two metaheuristic algorithms, a Genetic Algorithm (GA) and Ant Colony Optimization (ACO). The GA optimizes ACO parameters to find the optimal parameter settings automatically to solve a given Capacitated Vehicle Routing Problem (CVRP). The research design and the implemented prototype for this experiment are explained in detail and test results are presented. Optimal ACO parameters for the different CVRP are computed and analyzed and the reasonability of the proposed GA-ACO algorithm to solve CVRP is discussed.

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CITATION STYLE

APA

Faust, O. S., Mehli, C. G., Hanne, T., & Dornberger, R. (2020). A Genetic Algorithm for Optimizing Parameters for Ant Colony Optimization Solving Capacitated Vehicle Routing Problems. In ACM International Conference Proceeding Series (pp. 52–58). Association for Computing Machinery. https://doi.org/10.1145/3396474.3396489

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