Heuristic Multiobjective Search for Hazmat Transportation Problems

  • Enrique Machuca
  • Lawrence Mandow
  • José Luis Pérez de la Cruz
  • Antonio Iovanella
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7023)

Abstract

This paper describes the application of multiobjective heuristic search algorithms to the problem of hazardous material (hazmat) transportation. The selection of optimal routes inherently involves the consideration of multiple conflicting objectives. These include the minimization of risk (e.g. the exposure of the population to hazardous substances in case of accident), transportation cost, time, or distance. Multiobjective analysis is an important tool in hazmat transportation decision making. This paper evaluates the application of multiobjective heuristic search techniques to hazmat route planning. The efficiency of existing algorithms is known to depend on factors like the number of objectives and their correlations. The use of an informed multiobjective heuristic function is shown to significantly improve efficiency in problems with two and three objectives. Test problems are defined over random graphs and over a real road map.

Keywords

Random Graph Heuristic Search Hazardous Material Route Planning Heuristic Estimate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Enrique Machuca
    • 1
  • Lawrence Mandow
    • 1
  • José Luis Pérez de la Cruz
    • 1
  • Antonio Iovanella
    • 2
  1. 1.Dpto. Lenguajes y Ciencias de la ComputaciónUniversidad de MálagaMálagaSpain
  2. 2.Dipartimento di Ingegneria dell’ImpresaUniversity of Rome “Tor Vergata”RomeItaly

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