Local search study of honeycomb clustering problem for cellular planning. (6th September 2006)

• Record Type: Journal Article
• Authors: Creput, Jean-Charles; Koukam, Abderrafiaa
• Is Part Of: International journal of mobile network design and innovation. Volume 1:Number 2(2006)
• Page Start: 153
• Page End: 160
• Publication Date: 2006-09-06
• Subjects: cellular networks -- network dimensioning -- adaptive mesh generation -- evolutionary algorithms -- mobile networks -- local search -- honeycomb clustering -- cellular planning; Mobile communication systems -- Periodicals; Wireless communication systems -- Design and construction -- Periodicals; 384.535
• Languages: English
• ISSNs: 1744-2869

Abstract

We study a local search approach for a coverage problem in the plane, called Balanced Honeycomb Clustering Problem (BHCP), where a honeycomb mesh is used to build irregular hexagonal clusters that have to cover a fixed amount of points of a given data distribution. This problem has application to dimension cellular networks adapted to radio-mobile traffic. The local search approach uses dynamic application of fitness landscape penalties in order to exit local minima and improve performances, while eliminating overloaded cells. Results are given in comparison to best solutions known generated by an evolutionary algorithm. For a considerable reduction of computational time, about 3000% lower, we show that local search outperforms a population-based evolutionary approach.