文章基本信息

标题：QCA & CQCA: Quad Countries Algorithm and Chaotic Quad Countries Algorithm
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作者：M. A. Soltani-Sarvestani ; Shahriar Lotfi
期刊名称：Journal of Theoretical and Applied Computer Science
印刷版ISSN：2299-2634
电子版ISSN：2300-5653
出版年度：2012
卷号：6
期号：3
页码：3-20
出版社：Polska Akademia Nauk * Oddzial w Gdansku, Komisja Informatyki,Polish Academy of Sciences, Gdansk Branch, Computer Science Commission
摘要：This paper introduces an improved evolutionary algorithm based on the Imperialist Com-petitive Algorithm (ICA), called Quad Countries Algorithm (QCA) and with a little change called Chaotic Quad Countries Algorithm (CQCA). The Imperialist Competitive Algorithm is inspired by socio-political process of imperialistic competition in the real world and has shown its reliable performance in optimization problems. This algorithm converges quickly, but is easily stuck into a local optimum while solving high-dimensional optimization prob-lems. In the ICA, the countries are classified into two groups: Imperialists and Colonies which Imperialists absorb Colonies, while in the proposed algorithm two other kinds of countries, namely Independent and Seeking Independence countries, are added to the coun-tries collection which helps to more exploration. In the suggested algorithm, Seeking Inde-pendence countries move in a contrary direction to the Imperialists and Independent countries move arbitrarily that in this paper two different movements are considered for this group; random movement (QCA) and Chaotic movement (CQCA). On the other hand, in the ICA the Imperialists’ positions are fixed, while in the proposed algorithm, Imperialists will move if they can reach a better position compared to the previous position. The proposed algorithm was tested by famous benchmarks and the compared results of the QCA and CQCA with results of ICA, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Particle Swarm inspired Evolutionary Algorithm (PS-EA) and Artificial Bee Colony (ABC) show that the QCA has better performance than all mentioned algorithms. Between all cases, the QCA, ABC and PSO have better performance respectively about 50%, 41.66% and 8.33% of cases.
关键词：Optimization; Imperialist Competitive Algorithm (ICA); Independent country; Seeking Independent country; Quad Countries Algorithm (QCA) and Chaotic Quad Countries Algorithm (CQCA)