Abstract
In this work we present the practical application of the Asynchronous Situated Coevolution (ASiCo) algorithm to a special type of vehicle routing problem, the heterogeneous fleet vehicle routing problem with time windows (HVRPTW). It consists in simultaneously determining the composition and the routing of a fleet of heterogeneous vehicles in order to serve a set of time-constrained delivery demands. The ASiCo algorithm performs a situated coevolution process inspired on those typical of the Artificial Life field that has been improved with a strategy to guide the evolution towards a design objective. This strategy is based on the principled evaluation function selection for evolving coordinated multirobot systems developed by Agogino and Tumer. ASiCo has been designed to solve dynamic, distributed and combinatorial optimization problems in a completely decentralized way, resulting in an alternative approach to be applied to several engineering optimization domains where current algorithms perform unsatisfactorily.
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Prieto, A., Bellas, F., Caamaño, P., Duro, R.J. (2011). Solving a Heterogeneous Fleet Vehicle Routing Problem with Time Windows through the Asynchronous Situated Coevolution Algorithm. In: Kampis, G., Karsai, I., Szathmáry, E. (eds) Advances in Artificial Life. Darwin Meets von Neumann. ECAL 2009. Lecture Notes in Computer Science(), vol 5778. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21314-4_25
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DOI: https://doi.org/10.1007/978-3-642-21314-4_25
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