An optimization strategy based on the movement behavior of soccer players

博士 === 中原大學 === 工業與系統工程研究所 === 101 === 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 pla...

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Main Authors: Hindriyanto Dwipurnomo, 游漢杰
Other Authors: Hui-Ming Wee
Format: Others
Language:en_US
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/06570758707959347356
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spelling ndltd-TW-101CYCU50300162015-10-13T22:40:29Z http://ndltd.ncl.edu.tw/handle/06570758707959347356 An optimization strategy based on the movement behavior of soccer players 依據足球運動員的移動行為探討最佳化移動策略 Hindriyanto Dwipurnomo 游漢杰 博士 中原大學 工業與系統工程研究所 101 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. Hui-Ming Wee 黃惠民 2013 學位論文 ; thesis 187 en_US
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description 博士 === 中原大學 === 工業與系統工程研究所 === 101 === 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.
author2 Hui-Ming Wee
author_facet Hui-Ming Wee
Hindriyanto Dwipurnomo
游漢杰
author Hindriyanto Dwipurnomo
游漢杰
spellingShingle Hindriyanto Dwipurnomo
游漢杰
An optimization strategy based on the movement behavior of soccer players
author_sort Hindriyanto Dwipurnomo
title An optimization strategy based on the movement behavior of soccer players
title_short An optimization strategy based on the movement behavior of soccer players
title_full An optimization strategy based on the movement behavior of soccer players
title_fullStr An optimization strategy based on the movement behavior of soccer players
title_full_unstemmed An optimization strategy based on the movement behavior of soccer players
title_sort optimization strategy based on the movement behavior of soccer players
publishDate 2013
url http://ndltd.ncl.edu.tw/handle/06570758707959347356
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