Simplifying Fitness Landscapes Using Dilation Functions Evolved With Genetic Programming Daniele M. Papetti University ofMilano-Bicocca, ITALY Andrea Tangherloni University ofBergamo, ITALY Davide Farinati NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, PORTUGAL Digital Object Identifier 10.1109/MCI.2022.3222096 Date ofcurrent version: 13January 2023 22 IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | FEBRUARY 2023 Paolo Cazzaniga University ofBergamo, ITALY Leonardo Vanneschi NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, PORTUGAL Abstract-Several optimization problems have features that hinder the capabilities ofsearching heuristics. To cope with this 1556-603X ß 2023 IEEE ßSHUTTERSTOCK.COM/PROSTOCKSTUDIOhttp://www.SHUTTERSTOCK.COM/PROSTOCKSTUDIO https://orcid.org/0000-0002-3574-6027 https://orcid.org/0000-0001-7780-0434 https://orcid.org/0000-0002-5856-4453 https://orcid.org/0000-0003-4732-3328 https://orcid.org/0000-0003-2925-527X