An optimization algorithm for solving the rich vehicle routing problem based on Variable Neighborhood Search and Tabu Search metaheuristics

• Juan Antonio Sicilia ^[1] ; Carlos Quemada ^[3] ; Beatriz Royo ^[2] ; David Escuín ^[4]
  1. [1] Universidad Internacional de La Rioja

     Universidad Internacional de La Rioja

     Logroño, España

     
  2. [2] Universidad de Zaragoza

     Universidad de Zaragoza

     Zaragoza, España

     
  3. [3] State University in Blacksurg, Virginia, USA
  4. [4] Instituto Tecnológico de Aragón, Zaragoza, Spain

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• Localización: Journal of computational and applied mathematics, ISSN 0377-0427, Vol. 291, Nº 1 (1 January 2016), 2016, págs. 468-477
• Idioma: inglés
• DOI: 10.1016/j.cam.2015.03.050
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• Resumen

  • This paper presents a novel optimization algorithm that consists of metaheuristic processes to solve the problem of the capillary distribution of goods in major urban areas taking into consideration the features encountered in real life: time windows, capacity constraints, compatibility between orders and vehicles, maximum number of orders per vehicle, orders that depend on the pickup and delivery and not returning to the depot. With the intention of reducing the wide variety of constraints and complexities, known as the Rich Vehicle Routing Problem, this algorithm proposes feasible alternatives in order to achieve the main objective of this research work: the reduction of costs by minimizing distances and reducing the number of vehicles used as long as the service quality to customers is optimum and a load balance among vehicles is maintained.