CLOVES

CLOVES: a cluster-and-search heuristic to solve the vehicle routing problem with delivery and pick-up This paper addresses the vehicle routing problem with sequence-constrained delivery and pick-up (VRPDP). We propose a multi-phase constructive heuristic that clusters nodes based on proximity, orients them along a route using shrink-wrap algorithm and allots vehicles using generalized assignment procedure. We employ genetic algorithm for an intensive final search. Trials on a large number of test-problems have yielded encouraging results.


References in zbMATH (referenced in 10 articles , 1 standard article )

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  1. Emeç, Uğur; Çatay, Bülent; Bozkaya, Burcin: An adaptive large neighborhood search for an E-grocery delivery routing problem (2016)
  2. Jauhar, Sunil Kumar; Pant, Millie: Genetic algorithms in supply chain management: a critical analysis of the literature (2016)
  3. Yin, Peng-Yeng; Chuang, Ya-Lan: Adaptive memory artificial bee colony algorithm for Green vehicle routing with cross-docking (2016)
  4. Yanik, Seda; Bozkaya, Burcin; deKervenoael, Ronan: A new VRPPD model and a hybrid heuristic solution approach for e-tailing (2014)
  5. Ramkumar, N.; Subramanian, P.; Narendran, T. T.; Ganesh, K.: Mixed integer linear programming model for multi-commodity multi-depot inventory routing problem (2012)
  6. Hu, Xiangpei; Wang, Zheng; Huang, Minfang; Zeng, Amy Z.: A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure (2009)
  7. Potvin, Jean-Yves: State-of-the art review-evolutionary algorithms for vehicle routing (2009)
  8. Borgulya, István: An algorithm for the capacitated vehicle routing problem with route balancing (2008)
  9. Martinovic, Goran; Aleksi, Ivan; Baumgartner, Alfonzo: Single-commodity vehicle routing problem with pickup and delivery service (2008)
  10. Ganesh, K.; Narendran, T. T.: CLOVES: a cluster-and-search heuristic to solve the vehicle routing problem with delivery and pick-up (2007)