Parallel Imperialist Competitive Algorithms

The importance of optimization and NP-problem solving cannot be overemphasized. The usefulness

and popularity of evolutionary computing methods are also well established. There are

various types of evolutionary methods; they are mostly sequential but some of them have parallel

implementations as well.We propose a multi-population method to parallelize the Imperialist

CompetitiveAlgorithm. The algorithm has been implementedwith the Message Passing Interface

on 2 computer platforms, and we have tested our method based on shared memory and message

passing architectural models. An outstanding performance is obtained, demonstrating that

the proposed method is very efficient concerning both speed and accuracy. In addition, compared

with a set of existingwell-known parallel algorithms, our approach obtainsmore accurate results

within a shorter time period.