最佳化在科學、工程和經濟問題上是相當重要的方法。最佳化方法有很多種,因不斷產生的最佳化問題,其數量仍持續增加。基於足球運動員的動作行為,本研究提出一個新的最佳化方法;此新方法有兩個基本動作,用“離開”和“前進”控制廣域與集中搜尋;除了動作外,此演算法具有運動員替換程序,對附近的一組優良解進行搜尋;一般來說,本研究提出的方法闡述了進化演算法中的競爭和複製過程,具有群體智慧演算法之強大的資訊共享;實作的範例中提供連續和不連續的問題,實驗結果展現出本方法具有成為一個強大的最佳化方法之潛力。作為一種新方法,本演算法可用不同的方式來加強,例如:發展更多種類的球員動作,以及實施本方法來解決各種最佳化問題。
Optimization is important in science, engineering and economic problems. There are many optimization methods and their numbers increase continuously due to the growing optimization problems. A new optimization method based on the movement behavior of soccer players is proposed in this study. The new method has two basic movements; the move off and the move forward; which are used to control the diversification and intensification. Beside the movements, the algorithm has player substitution procedure which will impose the search process into nearby a set of goodsolution. In general, the proposed method elaborates the competition and the reproduction process in evolutionary algorithm with the powerful information sharing of swarm intelligence algorithm. Examples of implementations are provided for continuous and discrete problems. The experiment results reveal that the proposed method has the potential to become a powerful optimization method. As a new method, the proposed algorithm can be enhanced in many different ways such as elaborating more aspects of the soccer players’ movement as well as implementing the proposed method to solve various optimization problems.
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