Elsevier

SoftwareX

Volume 17, January 2022, 100961
SoftwareX

Original software publication
PyDDRBG: A Python framework for benchmarking and evaluating static and dynamic multimodal optimization methods

https://doi.org/10.1016/j.softx.2021.100961Get rights and content
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Abstract

PyDDRBG is a Python framework for generating tunable test problems for static and dynamic multimodal optimization. It allows for quick and simple generation of a set of predefined problems for non-experienced users, as well as highly customized problems for more experienced users. It easily integrates with an arbitrary optimization method. It can calculate the optimization performance when measured according to the robust mean peak ratio. PyDDRBG is expected to advance the fields of static and dynamic multimodal optimization by providing a common platform to facilitate the numerical analysis, evaluation, and comparison in these fields.

Keywords

Test problems
Benchmarking
Niching
Performance indicator

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