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dc.contributor.authorJeroen Corstjens
dc.contributor.authorDang, Nguyen
dc.contributor.authorDepaire, Benoît
dc.contributor.authorCaris, An
dc.contributor.authorDe Causmaeckers, Patrick
dc.identifier.citationJeroen Corstjens , Dang , N , Depaire , B , Caris , A & De Causmaeckers , P 2019 , ' A combined approach for analysing heuristic algorithms ' , Journal of Heuristics , vol. 25 , no. 10 , pp. 591–628 .
dc.identifier.otherPURE: 258216742
dc.identifier.otherPURE UUID: c50a0a06-1dbf-4e9c-be42-a0df64d9f975
dc.identifier.otherScopus: 85051635264
dc.identifier.otherORCID: /0000-0002-2693-6953/work/55643846
dc.description.abstractWhen developing optimisation algorithms, the focus often lies on obtaining an algorithm that is able to outperform other existing algorithms for some performance measure. It is not common practice to question the reasons for possible performance differences observed. These types of questions relate to evaluating the impact of the various heuristic parameters and often remain unanswered. In this paper, the focus is on gaining insight in the behaviour of a heuristic algorithm by investigating how the various elements operating within the algorithm correlate with performance, obtaining indications of which combinations work well and which do not, and how all these effects are influenced by the specific problem instance the algorithm is solving. We consider two approaches for analysing algorithm parameters and components—functional analysis of variance and multilevel regression analysis—and study the benefits of using both approaches jointly. We present the results of a combined methodology that is able to provide more insights than when the two approaches are used separately. The illustrative case studies in this paper analyse a large neighbourhood search algorithm applied to the vehicle routing problem with time windows and an iterated local search algorithm for the unrelated parallel machine scheduling problem with sequence-dependent setup times.
dc.relation.ispartofJournal of Heuristicsen
dc.rightsCopyright © 2018, Springer Science+Business Media, LLC, part of Springer Nature. This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at
dc.subjectFunctional analysis of varianceen
dc.subjectMultilevel regressionen
dc.subjectAlgorithm performanceen
dc.subjectVehicle routing problem with time windowsen
dc.subjectLarge neighbourhood searchen
dc.subjectIterated local searchen
dc.subjectUnrelated parallel machine scheduling problemen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQA76 Computer softwareen
dc.titleA combined approach for analysing heuristic algorithmsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.description.statusPeer revieweden

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