Automatic cell planning (ACP) is an optimization problem from the mobile telecommunications domain that addresses finding the location of the network antennae as well as their parameter settings in order to satisfy several cellular operator requirements. Due to its NP-hard complexity, evolutionary techniques have become popular for solving ACP instances. This article presents a survey of evolutionary algorithms (EAs) engineered for addressing ACP problems, analysing both the features of the considered ACP problem and the main aspects of the EAs used to solve them. The survey provides an up-to-date overview that is not limited to any particular kind of evolutionary approach, and comprises advanced algorithmic enhancements like hybridization and parallelization. The article ends by addressing some important issues and open questions that can be the subject of future research.
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