In mobile communication systems, location management deals with the location determination of users in a network. One of the strategies used in location management is to partition the network into location areas. Each location area consists of a group of cells. The goal of location management is to partition the network into a number of location areas such that the total paging cost and handoff (or update) cost is a minimum. Finding the optimal number of location areas and the corresponding configuration of the partitioned network is a difficult combinatorial optimization problem. This cell grouping problem is to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking is a minimum in location area wireless network. In fact, this is shown to be an NP-complete problem in an earlier study. In this paper, artificial bee colony (ABC) is developed and proposed to obtain the best/optimal group of cells for location area planning for location management system. The performance of the artificial bee colony (ABC) is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters. The important control parameter of ABC is only ‘Limit’ which is the number of trials after which a food source is assumed to be abandoned. Simulation results for 16, 36, and 64 cell grouping problems in wireless network show that the performance of our ABC is better than those alternatives such as ant colony optimization (ACO) and particle swarm optimization (PSO).