Projects per year
Abstract
This paper provides a taxonomical identification survey of classes in discrete optimization challenges that can be found in the literature including a proposed pipeline for benchmarking, inspired by previous computational optimization competitions. Thereby, a Black-Box Discrete Optimization Benchmarking (BB-DOB) perspective is presented for the BB-DOB@GECCO Workshop. It is motivated why certain classes together with their properties (like deception and separability or toy problem label) should be included in the perspective. Moreover, guidelines on how to select significant instances within these classes, the design of experiments setup, performance measures, and presentation methods and formats are discussed.
Original language | English |
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Title of host publication | GECCO '18 |
Subtitle of host publication | Proceedings of the Genetic and Evolutionary Computation Conference Companion |
Publisher | Association for Computing Machinery |
Pages | 1777-1782 |
Publication status | Published - 06 Jul 2018 |
Event | GECCO 2018: The Genetic and Evolutionary Computation Conference - Kyoto, Japan Duration: 15 Jul 2018 → 19 Jul 2018 http://gecco-2018.sigevo.org |
Conference
Conference | GECCO 2018: The Genetic and Evolutionary Computation Conference |
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Country/Territory | Japan |
City | Kyoto |
Period | 15 Jul 2018 → 19 Jul 2018 |
Internet address |
Fingerprint
Dive into the research topics of 'A Black-Box Discrete Optimization Benchmarking (BB-DOB) Pipeline Survey: Taxonomy, Evaluation, and Ranking'. Together they form a unique fingerprint.Projects
- 1 Finished
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Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice - ImAppNIO
09 Mar 2016 → 08 Mar 2020
Project: Externally funded research