TY - GEN

T1 - Algorithm selection on generalized quadratic assignment problem landscapes

AU - Beham, Andreas

AU - Wagner, Stefan

AU - Affenzeller, Michael

N1 - Publisher Copyright:
© 2018 Copyright held by the owner/author(s).
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Algorithm selection is useful in decision situations where among many alternative algorithm instances one has to be chosen. This is often the case in heuristic optimization and is detailed by the well-known no-free-lunch (NFL) theorem. A consequence of the NFL is that a heuristic algorithm may only gain a performance improvement in a subset of the problems. With the present study we aim to identify correlations between observed differences in performance and problem characteristics obtained from statistical analysis of the problem instance and from fitness landscape analysis (FLA). Finally, we evaluate the performance of a recommendation algorithm that uses this information to make an informed choice for a certain algorithm instance.

AB - Algorithm selection is useful in decision situations where among many alternative algorithm instances one has to be chosen. This is often the case in heuristic optimization and is detailed by the well-known no-free-lunch (NFL) theorem. A consequence of the NFL is that a heuristic algorithm may only gain a performance improvement in a subset of the problems. With the present study we aim to identify correlations between observed differences in performance and problem characteristics obtained from statistical analysis of the problem instance and from fitness landscape analysis (FLA). Finally, we evaluate the performance of a recommendation algorithm that uses this information to make an informed choice for a certain algorithm instance.

KW - Algorithm selection

KW - Assignment problems

KW - Fitness landscapes

UR - http://www.scopus.com/inward/record.url?scp=85050606379&partnerID=8YFLogxK

U2 - 10.1145/3205455.3205585

DO - 10.1145/3205455.3205585

M3 - Conference contribution

T3 - GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference

SP - 253

EP - 260

BT - GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference

PB - Association for Computing Machinery, Inc

T2 - 2018 Genetic and Evolutionary Computation Conference, GECCO 2018

Y2 - 15 July 2018 through 19 July 2018

ER -