A Hybrid Genetic Algorithm for the Rich Vehicle Routing Problem

نویسندگان

  • ISMAIL YUSUF
  • SAPIYAN BABA
  • NUR IKSAN
چکیده

This research present a set-partitioning heuristic to generate populations in a hybrid genetic algorithm (hGA) which is able to solve four different variants of the vehicle routing problem: the multi-depot vehicle routing problem (MDVRP), the heterogeneous fleet and mix decisions (type, size and number of vehicle) (HFMVRP), site dependent vehicle routing problem (SDVRP) and the asymmetric vehicle routing problem (AVRP). The goal is to find a set of routes with minimum fuel consumption and satisfying a number of predetermined constraints. Initial test results show that the route produced by hGA proposed effectively used for solve rich VRP and especially vehicle routing problem with a large number of customers, depots and vehicles. Key-Words: multi-depot, heterogeneous, site-dependent, asymmetric, clustering, set-partitioning, hybrid genetic algorithm.

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تاریخ انتشار 2012