Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems

April 14, 2020 ยท Declared Dead ยท ๐Ÿ› GECCO Companion

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Authors Koen van der Blom, Timo M. Deist, Tea Tuลกar, Mariapia Marchi, Yusuke Nojima, Akira Oyama, Vanessa Volz, Boris Naujoks arXiv ID 2004.06395 Category cs.NE: Neural & Evolutionary Citations 6 Venue GECCO Companion Last Checked 3 months ago
Abstract
Benchmarks are a useful tool for empirical performance comparisons. However, one of the main shortcomings of existing benchmarks is that it remains largely unclear how they relate to real-world problems. What does an algorithm's performance on a benchmark say about its potential on a specific real-world problem? This work aims to identify properties of real-world problems through a questionnaire on real-world single-, multi-, and many-objective optimization problems. Based on initial responses, a few challenges that have to be considered in the design of realistic benchmarks can already be identified. A key point for future work is to gather more responses to the questionnaire to allow an analysis of common combinations of properties. In turn, such common combinations can then be included in improved benchmark suites. To gather more data, the reader is invited to participate in the questionnaire at: https://tinyurl.com/opt-survey
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