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A hybrid genetic-GRASP algorithm using Lagrangean relaxation for the traveling salesman problem
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.
2005 (English)In: Journal of combinatorial optimization, ISSN 1382-6905, E-ISSN 1573-2886, Vol. 10, no 4, p. 311-326Article in journal (Refereed) Published
Abstract [en]

Hybridization techniques are very effective for the solution of combinatorial optimization problems. This paper presents a genetic algorithm based on Expanding Neighborhood Search technique (Marinakis, Migdalas, and Pardalos, Computational Optimization and Applications, 2004) for the solution of the traveling salesman problem: The initial population of the algorithm is created not entirely at random but rather using a modified version of the Greedy Randomized Adaptive Search Procedure. Farther more a stopping criterion based on Lagrangean Relaxation is proposed. The combination of these different techniques produces high quality solutions. The proposed algorithm was tested on numerous benchmark problems from TSPLIB with very satisfactory results. Comparisons with the algorithms of the DIMACS Implementation Challenge are also presented

Place, publisher, year, edition, pages
2005. Vol. 10, no 4, p. 311-326
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
URN: urn:nbn:se:ltu:diva-9684DOI: 10.1007/s10878-005-4921-7Local ID: 85841852-4727-4a0e-9ce7-042158eef9c7OAI: oai:DiVA.org:ltu-9684DiVA, id: diva2:982622
Note
Upprättat; 2005; 20140919 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-04-11Bibliographically approved

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Migdalas, Athanasios

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