Abstract:

This paper introduces the utilization of island harmony search in a parallel platform for optimization problems. The main purposes of this utilization is to reduce the computational time and memory resource required to find the optimal solution. Thus the search process of the island harmony search algorithm becomes more efficient. Harmony search (HS) algorithm is a metaheuristic optimization algorithm that imitates the natural phenomenon of musicians’ behaviors when collectively tuning the pitches of their instruments to achieve a pleasant harmony. In evolutionary algorithms, Island model is a structured population mechanism used to preserve the diversity of the population. In addition to its ability for controlling the diversity, island model can provide a suitable optimization framework to be utilized in a parallel platform. More specifically in this paper, two parallel model-based multicore techniques using shared memory are developed by taking advantage of the multithreading capabilities of parallel computing. The experiments will be conducted using a set of benchmark function to prove the efficiency of proposed parallel model.