Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21111
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dc.contributor.authorCORSTJENS, Jeroen-
dc.contributor.authorCARIS, An-
dc.contributor.authorDEPAIRE, Benoit-
dc.contributor.authorSörensen, Kenneth-
dc.date.accessioned2016-05-18T06:54:35Z-
dc.date.available2016-05-18T06:54:35Z-
dc.date.issued2016-
dc.identifier.citationEU/ME 2016 Workshop on Design and Analysis of Metaheuristics-
dc.identifier.urihttp://hdl.handle.net/1942/21111-
dc.description.abstractHeuristic algorithms for the vehicle routing problem are commonly assessed by using a competitive evaluation methodology. This may give an indication of which algorithm obtains a better performance, it does not explain, however, why it is better. The appliance of a proper statistical methodology can provide researchers a better understanding of how performance is affected by the different algorithmic parameters and heuristic components and result in a more robust parameter setting and scientific basis for comparison.-
dc.language.isoen-
dc.subject.otheralgorithm configuration; metaheuristics; statistical methodology; vehicle routing-
dc.titleA Multilevel Methodology for Analysing Metaheuristic Algorithms for the VRPTW-
dc.typeConference Material-
local.bibliographicCitation.conferencedateMarch 17-18, 2016-
local.bibliographicCitation.conferencenameEU/ME 2016 Workshop on Design and Analysis of Metaheuristics-
local.bibliographicCitation.conferenceplaceAntwerp, Belgium-
local.format.pages3-
local.bibliographicCitation.jcatC2-
dc.relation.referencesBirattari, M. (2009). Tuning Metaheuristics. Berlin, Heidelberg: Springer. Bräysy, O. and Gendreau, M. (2005a), Vehicle routing problem with time windows, part I: route construction and local search algorithms, Transportation Science, 39(1), pp. 104-118. Bräysy, O. and Gendreau, M. (2005b), Vehicle routing problem with time windows, part II: metaheuristics, Transportation Science, 39(1), pp. 119-139. Coy, S. P., Golden, B. L., Runger, G. C. and Wasil, E. A. (2000). Using experimental design to find effective parameter settings for heuristics. Journal of Heuristics, 7, pp. 77-97. Gelman, A., and Hill, J. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. Hooker, J. (1995). Testing Heuristics: We have it all wrong, Journal of Heuristics, 1(1), pp. 33-42. Hoos, H. H. (2011). Automated Algorithm Configuration and Parameter Tuning. In: Autonomous Search. s.l.:Springer Berlin Heidelberg, pp. 37-71. Montgomery, D. C. (2005). Design and Analysis of Experiments. 6th ed. s.l.:John Wiley and Sons Inc. Palhazi Cuervo, D., Goos, P., Sörensen, K., and Arráiz, E. (2014). An iterated local search algorithm for the vehicle routing problem with backhauls. European Journal of Operational Research, 237(2), pp. 454-464. Rardin, R. and Uzsoy, R. (2001). Experimental evaluation of heuristic optimization algorithms: A tutorial. Journal of Heuristics, 7, pp. 261-304. Sörensen, K. and Schittekat, P. (2013). Statistical analysis of distance-based path relinking for the capacitated vehicle routing problem. Computer & Operations Research, 40(12), pp. 3197-3205.-
local.type.refereedNon-Refereed-
local.type.specifiedPresentation-
item.fullcitationCORSTJENS, Jeroen; CARIS, An; DEPAIRE, Benoit & Sörensen, Kenneth (2016) A Multilevel Methodology for Analysing Metaheuristic Algorithms for the VRPTW. In: EU/ME 2016 Workshop on Design and Analysis of Metaheuristics.-
item.accessRightsOpen Access-
item.contributorCORSTJENS, Jeroen-
item.contributorCARIS, An-
item.contributorDEPAIRE, Benoit-
item.contributorSörensen, Kenneth-
item.fulltextWith Fulltext-
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