An adaptive heuristic optimization algorithm based on politics

Abstract

Heuristic optimization is used to tune parameters in various scientific fields. Therefore, a successful optimization algorithm that must be able to evolve in a parsimonious manner in many situations is necessary. Often, heuristic optimization algorithms are inspired by nature but imperialist competitive algorithm, inspired by the laws and policies governing human society, was presented in recent decade. Imperialist competitive algorithm was applied in various fields. This algorithm had a very good performance compared to other optimization algorithms. For this reason, this study tries to modify imperialist competitive algorithm for improve the accuracy and performance of the algorithm. Assimilation operator of the imperialist competitive algorithm is modified. The main motivation of this work is to introduce a powerful heuristic optimization algorithm. A comparison between the proposed imperialist competitive algorithm framework and several versions imperialist competitive algorithm on 6 standard numerical benchmarks and four famous optimization algorithm indicate that the proposed algorithm has a good performance on a wide variety of problems.

Keywords

Evolutionary algorithm optimization algorithm imperialist competitive algorithm assimilation policy

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