Andre Luis Silva
Felipe Campelo
ABSTRACT
We examine the performance of four discrete differential evolution (DE) algorithms for the solution of capacitated vehicle routing problems (CVRPs). Twenty seven test instances are employed in the experimental analysis, with comparisons of final solution quality and time to convergence. The results indicate that two approaches presented significantly better results, but that all algorithms are still lacking in their ability to converge to the vicinity of the global optimum.
- L. Assis, A. Maravilha, A. Vivas, F. Campelo, and J. Ramírez. Multiobjective vehicle routing problem with fixed delivery and optional collections. Optimization Letters, 6:1--13, 2012.Google Scholar
- P. Augerat, J., E. Benavent, A. Corbern, D. Naddef, and G. Rinaldi. Computation results with a branch and cut code for the capacited vehicle routing problem. Technical report, Univesite Joseph Fourier, Grenoble, France, 1995.Google Scholar
- M. Crawley. The R Book. John Wiley & Sons, Chichester, England, 1st. edition, 2007. Google ScholarCross Ref
- G. B. Dantzig and J. H. Ramser. The truck dispatching problem. Management Science, 6(1):80--91, October 1959.Google ScholarDigital Library
- B. L. Golden, S. Raghavan, and E. A. Wasil. The Vehicle Routing Problem: Latest Advances and New Challenges. Springer, 2008.Google ScholarCross Ref
- L. Jian-Jun and L. Jian. Solving capacitated vehicle routing problems by modified differential evolution. In 2nd International Asia Conference on Informatics in Control, Automation and Robotics, pages 513--516. Industrial Electronics Society (IE), March 2010. Google ScholarDigital Library
- G. Laporte. The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59(3):345--358, June 1992.Google ScholarCross Ref
- L. Mingyong and C. Erbao. An improved differential evolution algorithm for vehicle routing problem with simultaneous pickups and deliveries and time windows. Engineering Applications of Artificial Intelligence, 23(2):188--195, March 2010. Google ScholarDigital Library
- D. Montgomery. Design and Analysis of Experiments. Wiley, 2008.Google ScholarDigital Library
- G. C. Onwubolu and D. Davendra. Differential Evolution: a handbook for global permutation-based combinatorial optimization. Springer, Berlin, 2009. Google ScholarDigital Library
- A. Rachman, A. Dhini, and N. Mustafa. Vehicle routing problems with differential evolution algorithm to minimize cost. In The 20th National Conference of Australian Society for Operations Research, pages 78--91. Australian Society for Operations Research (ASOR), September 2009.Google Scholar
- R. Storn and K. Price. Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces. In TR-95-012, pages 1--12. ICSI, March 1995.Google Scholar
- P. Toth and D. Vigo. Models, relaxations and exact approaches for the capacitated vehicle routing problem. Discrete Applied Mathematics, 123(1-3):487--512, November 2002. Google ScholarDigital Library
- T. V. Web. Definition of the problem instances: Augerat test set, 2007.Google Scholar
Index Terms
- A statistical study of discrete differential evolution approaches for the capacitated vehicle routing problem.
Recommendations
A New Hybridization of Evolutionary Algorithms, GRASP and Set-Partitioning Formulation for the Capacitated Vehicle Routing Problem
Intelligent SystemsAbstractThis work presents a new hybrid method based on the route-first-cluster-second approach using Greedy Randomized Adaptive Search Procedure (GRASP), Differential Evolution (DE), Evolutionary Local Search (ELS) and set-partitioning problem (SPP) to ...
Population size reduction for the differential evolution algorithm
This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually ...
Constrained differential evolution with multiobjective sorting mutation operators for constrained optimization
The proposed constrained differential evolution framework uses nondominated sorting mutation operator based on fitness and diversity information for constrained optimization. This study proposes a new constraint differential evolution framework.Parents ...
Comments