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Identifying minimal set of Exploratory Landscape Analysis features for reliable algorithm performance prediction.

, , , , and . CEC, page 1-8. IEEE, (2022)

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GECCO black-box optimization competitions: progress from 2009 to 2018., , and . GECCO (Companion), page 275-276. ACM, (2019)Statistical analyses for meta-heuristic stochastic optimization algorithms: GECCO 2020 tutorial., and . GECCO Companion, page 724-746. ACM, (2020)A Distributed Multilevel Ant-Colony Approach for Finite Element Mesh Decomposition., , and . PPAM (2), volume 6068 of Lecture Notes in Computer Science, page 398-407. Springer, (2009)Data-Driven Preference-Based Deep Statistical Ranking for Comparing Multi-objective Optimization Algorithms., , and . BIOMA, volume 10835 of Lecture Notes in Computer Science, page 138-150. Springer, (2018)A multi-objective approach to the application of real-world production scheduling., , and . Expert Syst. Appl., 40 (15): 5839-5853 (2013)Comparing multi-objective optimization algorithms using an ensemble of quality indicators with deep statistical comparison approach., , and . SSCI, page 1-8. IEEE, (2017)A Distributed Multilevel Ant Colonies Approach., , and . Informatica (Slovenia), 32 (3): 307-317 (2008)Data Mining-Assisted Parameter Tuning of a Search Algorithm., , and . Informatica (Slovenia), (2015)The Effect of Sampling Methods on the Invariance to Function Transformations When Using Exploratory Landscape Analysis., , and . CEC, page 1139-1146. IEEE, (2021)The differential ant-stigmergy algorithm: an experimental evaluation and a real-world application., , , and . IEEE Congress on Evolutionary Computation, page 157-164. IEEE, (2007)