A distributed metaheuristic for solving a real-world scheduling-routing-loading problem

  • Authors:

  • Laura Cruz Reyes;Juan Javier González Barbosa;David Romero Vargas;Hector Joaquin Fraire Huacuja;Nelson Rangel Valdez;Juan Arturo Herrera Ortiz;Bárbara Abigail Arrañaga Cruz;José Francisco Delgado Orta

  • Affiliations:

  • Instituto Tecnológico de Ciudad Madero, México;Instituto Tecnológico de Ciudad Madero, México;Instituto Tecnológico de Ciudad Madero, México;Instituto Tecnológico de Ciudad Madero, México;Instituto Tecnológico de Ciudad Madero, México;Instituto Tecnológico de Ciudad Madero, México;Instituto Tecnológico de Ciudad Madero, México;Instituto Tecnológico de Ciudad Madero, México

  • Venue:
  • ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications
  • Year:
  • 2007

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Abstract

In this paper a real and complex transportation problem including routing, scheduling and loading tasks is presented. Most of the related works only involve the solution of routing and scheduling, as a combination of up to five different types of VRPs (Rich VRP), leaving away the loading task, which are not enough to define more complex real-world cases. We propose a solution methodology for transportation instances that involve six types of VRPs, a new constraint that limits the number of vehicles that can be attended simultaneously and the loading tasks. They are solved using an Ant Colony System algorithm, which is a distributed metaheuristic. Results from a computational test using real-world instances show that the proposed approach outperforms the transportation planning related to manual designs. Besides a well-known VRP benchmark was solved to validate the approach.