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A Hybrid Clonal Selection Algorithm for the Vehicle Routing Problem with Stochastic Demands
School of Production Engineering and Management, Technical University of Crete, Decision Support Systems Laboratory, Department of Production Engineering and Management, Technical University of Crete.
Decision Support Systems Laboratory, Department of Production Engineering and Management, Technical University of Crete.ORCID iD: 0000-0001-8473-3663
Department of Industrial and Systems Engineering, Center for Applied Optimization, University of Florida.
2014 (English)Conference paper, Oral presentation only (Other academic)
Abstract [en]

The Clonal Selection Algorithm is the most known algo-rithm inspired from the Artificial Immune Systems and used effectivelyin optimization problems. In this paper, this nature inspired algorithmis used in a hybrid scheme with other metaheuristic algorithms for suc-cessfully solving the Vehicle Routing Problem with Stochastic Demands(VRPSD). More precisely, for the solution of this problem, the HybridClonal Selection Algorithm (HCSA) is proposed which combines a ClonalSelection Algorithm (CSA), a Variable Neighborhood Search (VNS), andan Iterated Local Search (ILS) algorithm. The effectiveness of the orig-inal Clonal Selection Algorithm for this NP-hard problem is improvedby using ILS as a hypermutation operator and VNS as a receptor edit-ing operator. The algorithm is tested on a set of 40 benchmark instancesfrom the literature and ten new best solutions are found. Comparisons ofthe proposed algorithm with several algorithms from the literature (twoversions of the Particle Swarm Optimization algorithm, a DifferentialEvolution algorithm and a Genetic Algorithm) are also reported.

Place, publisher, year, edition, pages
2014.
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
URN: urn:nbn:se:ltu:diva-35877Local ID: a95a7047-b97b-43f3-aa86-7fc647325307OAI: oai:DiVA.org:ltu-35877DiVA, id: diva2:1009131
Conference
Learning and Intelligent Optimization Conference : 16/02/2014 - 21/02/2014
Note
Upprättat; 2014; 20141117 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-04-11Bibliographically approved

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Migdalas, Athanasios
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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