A grouping biogeography-based optimization for location area planning

作者：Kim Sung Soo; Byeon Ji Hwan; Lee Seokcheon; Liu Hongbo^*

来源：Neural Computing & Applications, 2015, 26(8): 2001-2012.

DOI：10.1007/s00521-015-1856-5

• Biogeography-based optimization (BBO)
• Location area planning (LAP)
• Mobile computing
• Nature-inspired optimization

Location area planning (LAP) is a combinatorial optimization grouping problem for the cellular mobile network. We propose a novel grouping biogeography-based optimization (GBBO), which has suitable migration and mutation with generating good initial habitats to partition the optimal number of location areas. The migration is to move the whole cells of location area (LA) with a randomly selected cell between habitats for emigration and immigration, while the adjacent cell mutation is carried out between LAs within one habitat. These group migration and mutation mechanisms are available to maintain the grouping conditions. This proposed GBBO helps us to obtain the optimal number of location areas and the corresponding configuration of the partitioned network. We also illustrate the GBBO approach using the small, medium, and large size problems to compare with artificial bee colony, particle swarm optimization, and previous LAP methods. The experimental results show that our novel GBBO is robust to find the best configurations of LAP with much less computation time comparing with other considered methods.

• 出版日期2015-11