GVR Delivers It On Time
Authors
Abstract
Genetic Vehicle Representation (GVR) is a new two-levelrepresentational scheme designed to encode all the
information required by potential solutions for the vehicle
routing problem. In a previous paper we described a set of
experiments performed with several instances from the
Capacitated Vehicle Routing Problem (CVRP). In this
preliminary investigation, GVR proved to be both
effective and robust.
In this work we extend the application of this new genetic
representation to the vehicle routing problem with time
windows, a variant that adds additional time constraints to
the original definition. We present the results of a
comprehensive set of tests that show that GVR is also
efficient with this alternative, allowing the evolutionary
computation algorithm to reach optimal solutions for some
well know benchmarks.
Keywords
Representations, Vehicle Routing Problem, Time WindowsSubject
Evolutionary OptimizationCited by
Year 2011 : 1 citations
Ziauddin Ursani, Daryl Essam, David Cornforth, Robert Stocker, Localized genetic algorithm for vehicle routing problem with time windows, Applied Soft Computing, Volume 11, Issue 8, December 2011, Pages 5375-5390, ISSN 1568-4946
Year 2010 : 2 citations
Naoto Mukai and Kosuke Kawamura, "Simulation evaluation for on-demand bus system with electrical vehicles", Intelligent Decision Technologies, Vol.4, N. 4, pp.307-314, 2010, DOI - 10.3233/IDT-2010-0092
— J. E. Mendoza, B. Castanier, C. Guéret, A. L. Medaglia, and N. Velasco. A memetic algorithm for the multi-compartment vehicle routing problem with stochastic demands. Computers & Operations Research, 37(11):1886–1898, 2010
Year 2009 : 4 citations
JY Potvin. State-of-the Art Review—Evolutionary Algorithms for Vehicle Routing. INFORMS Journal on Computing, 2009.
Z Ursani, D Essam, D Cornforth, R Stocker, Introducing the localized genetic algorithm for small scale capacitated vehicle routing problems. INFOR: Information Systems and Operational Research, 2009.
— J. Mendoza, A. Medaglia, and N. Velasco. An evolutionary-based decision support system for vehicle routing: The case of a public utility. Decision Support Systems, 46(3):730–742, 2009;
**Potvin, Jean-Yves. A review of bio-inspired algorithms for vehicle routing. Springer Berlin Heidelberg, 2009.
Year 2008 : 5 citations
A. J. Pohl and G. B. Lamont. Multi-objective uav mission planning using evolutionary computa- tion. In S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, and J. W. Fowler, editors, Winter Simulation Conference, pages 1268–1279. WSC, 2008;
J.-Y. Potvin. A review of bio-inspired algorithms for vehicle routing. Technical Report CIRRELT- 2008-30, Inter university Research Centre on Enterprise Networks, Logistics and Transportation, July 2008;
N. Suthikarnnarunai. A sweep algorithm for the mix fleet vehicle routing problem. In Proce- edings of the International MultiConference of Engineers and Computer Scientists, volume IIIMECS 2008, Hong Kong, March 2008;
G. Lamont. Uav swarm mission planning development using evolutionary algorithms - part ii. NATO-RTO SCI-195 Lecture Series, 2008. University of Strathclyde, Glasgow;
J.-Y. Potvin. A review of bio-inspired algorithms for vehicle routing. In F. B. Pereira and J. Tavares, editors, Bio-inspired Algorithms for the Vehicle Routing Problem, volume 161 of Studies in Computational Intelligence, pages 1–34. Springer, 2008;
Year 2007 : 1 citations
Jean-Yves Potvin, Evolutionary Algorithms for Vehicle Routing, Technical Report CIRRELT-2007-48, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), November, 2007.
Year 2006 : 5 citations
A. R. Alexander Grakovski and A. Medvedev. Optimisation of operational routing for sup- ply chain on the basis of genetic algorithms. In Proceedings of the 6th International Conference Reliability and Statistics in Transportation and Communication, 2006;
N. B. Fabien Tricoire and P. Guez. Applications d’algorithmes d’optimisation pour la determi- nation de la politique d’organisation des tournees de service. In 6e Conference Francophone de MOdelisation et SIMulation - MOSIM’06, 2006;
A. R. Alexander Grakovski and A. Medvedev. Vehicle routing problem for city services solution by hybrid genetic algorithm. In Proceedings of the 6th International Conference Reliability and Statistics in Transportation and Communication, 2006;
A. G. Daiva Griškeviciené. Sustainability of vilnius public transport system by the integration of all modes of passenger conveyance. In Proceedings of the 6th International Conference Reliability and Statistics in Transportation and Communication, 2006;
J. N. Slear. Afit uav swarm mission planning and simulation system. Master’s thesis, Depart- ment of the Air Force, Air University, Air Force Institute of Technology, Wright-Patterson Air Force Base, June 2006;
Year 2005 : 5 citations
C.-H. Tseng. Theory and implementation of an intelligent vehicle dispatching system. Master’s thesis, Graduate Institute of Information Engineering, Feng Chia University, Taiwan, 2005;
M. A. Russell and G. B. Lamont. A genetic algorithm for unmanned aerial vehicle routing. Proceedings of the 2005 conference on Genetic and evolutionary computation GECCO 05, page 1523, 2005;
J. Schönberger. Operational Freight Carrier Planning: Basic Concepts, Optimization Models and Advanced Memetic Algorithms. Springer, 2005;
M. Russel. A genetic algorithm for uav routing integrated with a parallel swarm simulation. Master’s thesis, Department of the Air Force Air University, Air Force Institute of Technology, Wright-Patterson Air Force Base, 2005;
A. G. Qureshi. Analysis of the Effects of Cooperative Delivery System in Bangkok. PhD thesis, SCE : School of Civil Engineering, Asian Institute of Technology, Klong Luang, Thailand, 2005;
Year 2004 : 1 citations
Keng Hoo Chuah, "Optimization and Simulation of Just in Time Supply and Delivery Systems", PhD Thesis, College of Engineering at the University of Kentucky, January 2004.
Year 2003 : 1 citations
Wei-Che Chuang, An Inheritable Heuristic Algorithm for Bi-criteria Vehicle Routing Optimization Problems with Time Windows, Master's Thesis, Graduate Institute of Information Engineering, Feng Chia University, Taiwan, 2003.
Year 2002 : 1 citations
A. Tighe, and F. Smith, A Review of Artificial Intelligence Techniques in Fleet Logistics, Technical Report NUIG-IT-091002, Department of Information Technology, National University of Ireland, Galway, Ireland, 2002.