A hybrid metaheuristic algorithm for the vehicle routing problem with simultaneous delivery and pick-up service

  • Authors:

  • Emmanouil E. Zachariadis;Christos D. Tarantilis;Chris T. Kiranoudis

  • Affiliations:

  • Department of Process Analysis and Plant Design, National Technical University of Athens, Athens, Greece;Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece;Department of Process Analysis and Plant Design, National Technical University of Athens, Athens, Greece

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

This article addresses a vehicle routing problem variant which considers customers to require simultaneous delivery and pick-up service (VRPSPD). The objective of this problem is to determine the optimal set of routes to totally satisfy both the delivery and pick-up demand of the customer population. VRPSPD is an NP-hard combinatorial optimization problem; therefore exact methods are incapable of dealing with large scale VRPSPD instances arising in a wide variety of practical operations. We propose a hybrid solution approach incorporating the rationale of two well-known metaheuristics which have proven to be effective for routing problem variants, namely tabu search and guided local search. The intelligence of the proposed hybrid was designed to achieve a vast exploration of the search space, by escaping from local optima and intensifying at promising solution regions. The performance of our metaheuristic algorithm was tested on benchmark instances involving from 50 to 400 customers. It produced high quality results, improving several best solutions previously reported.