Salcedo-Sanz, SanchoGarcia-Diaz, PilarDel Ser, JavierBilbao, Miren NekanePortilla-Figueras, Jose Antonio2016-08-15Salcedo-Sanz , S , Garcia-Diaz , P , Del Ser , J , Bilbao , M N & Portilla-Figueras , J A 2016 , ' A novel Grouping Coral Reefs Optimization algorithm for optimal mobile network deployment problems under electromagnetic pollution and capacity control criteria ' , unknown , vol. unknown , pp. 388-402 . https://doi.org/10.1016/j.eswa.2016.02.032researchoutputwizard: 11556/144Publisher Copyright: © 2016 Elsevier Ltd. All rights reserved.This paper proposes a novel optimization algorithm for grouping problems, the Grouping Coral Reefs Optimization algorithm, and describes its application to a Mobile Network Deployment Problem (MNDP) under four optimization criteria. These criteria include economical cost and coverage, and also electromagnetic pollution control and capacity constraints imposed at the base stations controllers, which are novel in this study. The Coral Reefs Optimization algorithm (CRO) is a recently-proposed bio-inspired approach for optimization, based on the simulation of the processes that occur in coral reefs, including reproduction, fight for space or depredation. This paper presents a grouping version of the CRO, which has not previously evaluated before. Grouping meta-heuristics are characterized by variable-length encoding solutions, and have been successfully applied to a number of different optimization and assignment problems. The GCRO proposed is a novel contribution to the intelligent systems field, which is able to improve results obtained by two alternative grouping algorithms such as grouping genetic algorithms and grouping Harmony Search. The performance of the proposed GCRO and the algorithms for comparison has been tested with real data in a case study of a MNDP in Alcalá de Henares, Madrid, Spain.152859654enginfo:eu-repo/semantics/restrictedAccessjournal article10.1016/j.eswa.2016.02.032Coral Reefs OptimizationMobile network deploymentGrouping-based heuristicsElectromagnetic pollution minimizationBTS capacityCoral Reefs OptimizationMobile network deploymentGrouping-based heuristicsElectromagnetic pollution minimizationBTS capacityGeneral EngineeringComputer Science ApplicationsArtificial IntelligenceSDG 14 - Life Below WaterFunding InfoSpanish Ministerial Commission of Science and Technology (MICYT), TIN2014-54583-C2-2-R_x000D_ Comunidad Autónoma de Madrid, S2013ICE-2933_02Spanish Ministerial Commission of Science and Technology (MICYT), TIN2014-54583-C2-2-R_x000D_ Comunidad Autónoma de Madrid, S2013ICE-2933_02http://www.scopus.com/inward/record.url?scp=84960155930&partnerID=8YFLogxK