Evolution of vehicle routing problem heuristics with genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Gulic:2013:MIPRO,
  author =       "Matija Gulic and Domagoj Jakobovic",
  booktitle =    "36th International Convention on Information
                 Communication Technology Electronics Microelectronics
                 (MIPRO 2013)",
  title =        "Evolution of vehicle routing problem heuristics with
                 genetic programming",
  year =         "2013",
  month =        "20-24 " # may,
  pages =        "988--992",
  keywords =     "genetic algorithms, genetic programming, vehicle
                 routing problem with time windows",
  URL =          "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6596400",
  abstract =     "Increasingly complex variants of the vehicle routing
                 problem with time windows (VRPTW) are coming into
                 focus, alleviated with advances in the computing power.
                 VRPTW is a combination of the classical travelling
                 salesman and bin packing problems, with many real world
                 applications in various fields - from physical resource
                 manipulation planning to virtual resource management in
                 the ever more popular cloud computing domain. The basis
                 for many VRPTW approaches is a heuristic which builds a
                 candidate solution that is subsequently improved by a
                 search or optimisation procedure. The choice of the
                 appropriate heuristic may have a great impact on the
                 resulting quality of the obtained schedules. In this
                 paper we use genetic programming to evolve a suitable
                 heuristic to build initial solutions for different
                 objectives and classes of VRPTW instances. The results
                 show great potential, since this method is applicable
                 to different problem classes and user-defined
                 performance objectives.",
  notes =        "Also known as \cite{6596400}",
}

Genetic Programming entries for Matija Gulic Domagoj Jakobovic

Citations