Discrete real-world problems in a black-box optimization benchmark

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Abstract

Combinatorial optimization problems come in a wide variety of types but five common problem components can be identified. This categorization can aid the selection of interesting and diverse set of problems for inclusion in the combinatorial black-box problem benchmark. We suggest two real-world problems for inclusion into the benchmark. One is a transport-lot building problem and the other one is the clustered generalized quadratic assignment problem. We look into designing an interface for discrete black-box problems that can accommodate problems belonging to all of the described categories as well real-world problems that often feature multiple problem components. We describe three different interfaces for black-box problems, the first using a general encoding for all types of problems the second one using specialized encodings per problem type and the last one describes problems in terms of the available operators. We compare the strengths and weaknesses of the three designs.

Original languageEnglish
Title of host publicationGECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages1745-1752
Number of pages8
ISBN (Electronic)9781450357647
DOIs
Publication statusPublished - 6 Jul 2018
Event2018 Genetic and Evolutionary Computation Conference, GECCO 2018 - Kyoto, Japan
Duration: 15 Jul 201819 Jul 2018

Publication series

NameGECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion

Conference

Conference2018 Genetic and Evolutionary Computation Conference, GECCO 2018
CountryJapan
CityKyoto
Period15.07.201819.07.2018

Keywords

  • Benchmark design
  • Black-box optimization
  • Real-world problems

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