A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery


Goksal F. P., KARAOĞLAN İ., ALTIPARMAK BAYKOÇ F.

COMPUTERS & INDUSTRIAL ENGINEERING, cilt.65, sa.1, ss.39-53, 2013 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 65 Sayı: 1
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1016/j.cie.2012.01.005
  • Dergi Adı: COMPUTERS & INDUSTRIAL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.39-53
  • Anahtar Kelimeler: Vehicle routing problem, Simultaneous pickup and delivery, Particle swarm optimization, Variable neighborhood descent algorithm, METAHEURISTIC ALGORITHM, HEURISTIC ALGORITHMS, SINGLE
  • Gazi Üniversitesi Adresli: Evet

Özet

Vehicle routing problem (VRP) is an important and well-known combinatorial optimization problem encountered in many transport logistics and distribution systems. The VRP has several variants depending on tasks performed and on some restrictions, such as time windows, multiple vehicles, backhauls, simultaneous delivery and pick-up, etc. In this paper, we consider vehicle routing problem with simultaneous pickup and delivery (VRPSPD). The VRPSPD deals with optimally integrating goods distribution and collection when there are no precedence restrictions on the order in which the operations must be performed. Since the VRPSPD is an NP-hard problem, we present a heuristic solution approach based on particle swarm optimization (PSO) in which a local search is performed by variable neighborhood descent algorithm (VND). Moreover, it implements an annealing-like strategy to preserve the swarm diversity. The effectiveness of the proposed PSO is investigated by an experiment conducted on benchmark problem instances available in the literature. The computational results indicate that the proposed algorithm competes with the heuristic approaches in the literature and improves several best known solutions. (C) 2012 Elsevier Ltd. All rights reserved.