Volume 15, Number 6

A Hybrid GAPSO Optimization Approach


Lutfi Mohammed Omer Khanbary, Aden University, Yemen


In this work, the hybrid techniques of genetic algorithm (GA) and particle swarm optimization (PSO) are presented. PSO and GA are two population-based heuristic search methods that can be applied to the channel allocation optimization problem. GAPSO is based on a mixture of particle swarm optimization (PSO) and genetic algorithms (GA). Individuals of a new generation are produced in GAPSO by PSO in addition to crossover and mutation operations as in GA. In order to reduce the number of blocked calls and handoff failures in the mobile network, the Hybrid GAPSO algorithm is used to allocate tasks to resources efficiently. The proposed strategy optimizes the channel allocation using the GAPSO.


channel allocation; evolutionary algorithm; genetic algorithms; particle swarm optimization.