Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems
碩士 === 國立暨南國際大學 === 資訊工程學系 === 104 === Meta-heuristic is one of the popular research which is implemented to solve optimization problems in real life. In order to obtain the best solution in limited cost or time, traditional meta-Heuristics are devoted to balancing the capabilities of exploration an...
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ndltd-TW-104NCNU03920142017-08-27T04:30:06Z http://ndltd.ncl.edu.tw/handle/57421545845830732890 Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems 美洲豹演算法結合自適應領地跳脫機制解方程式最佳化問題 TSAI, YUNG-CHE 蔡永哲 碩士 國立暨南國際大學 資訊工程學系 104 Meta-heuristic is one of the popular research which is implemented to solve optimization problems in real life. In order to obtain the best solution in limited cost or time, traditional meta-Heuristics are devoted to balancing the capabilities of exploration and exploitation. For the sake of the purpose, traditional methods implement lots of weights (parameters) to balance two capabilities, and implement random variables or numerous population and generation to increase opportunities for finding a better solution. However, the searching mode of traditional methods might have some potential problems. Such as exploration and exploitation in traditional methods might restrict to each other. And implemented parameters shall be adjusted for different problems. Therefore, Jaguar Algorithm is designed in a new concept. We concentrate on exploitation before exploration. At first, proposed method tries its best to find the optimal solution in the arbitrary area. Then it focuses on jumping to better area based on the information of the history. Along the tendency of found areas to find out the place of the global optimum. Proposed method achieves strong capabilities of both exploitation and exploration with these features. Implement adaptive method to adjust approximate parameter according to different problems. The self-analysis and experiment of this research reveal that each capability of Jaguar Algorithm could have various positive effects. And the comparison with traditional meta-heuristics shows outstanding performance of Jaguar Algorithm by benchmark functions. 周耀新 2016 學位論文 ; thesis 48 en_US |
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碩士 === 國立暨南國際大學 === 資訊工程學系 === 104 === Meta-heuristic is one of the popular research which is implemented to solve optimization problems in real life. In order to obtain the best solution in limited cost or time, traditional meta-Heuristics are devoted to balancing the capabilities of exploration and exploitation. For the sake of the purpose, traditional methods implement lots of weights (parameters) to balance two capabilities, and implement random variables or numerous population and generation to increase opportunities for finding a better solution. However, the searching mode of traditional methods might have some potential problems. Such as exploration and exploitation in traditional methods might restrict to each other. And implemented parameters shall be adjusted for different problems. Therefore, Jaguar Algorithm is designed in a new concept. We concentrate on exploitation before exploration. At first, proposed method tries its best to find the optimal solution in the arbitrary area. Then it focuses on jumping to better area based on the information of the history. Along the tendency of found areas to find out the place of the global optimum. Proposed method achieves strong capabilities of both exploitation and exploration with these features. Implement adaptive method to adjust approximate parameter according to different problems. The self-analysis and experiment of this research reveal that each capability of Jaguar Algorithm could have various positive effects. And the comparison with traditional meta-heuristics shows outstanding performance of Jaguar Algorithm by benchmark functions.
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周耀新 |
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周耀新 TSAI, YUNG-CHE 蔡永哲 |
author |
TSAI, YUNG-CHE 蔡永哲 |
spellingShingle |
TSAI, YUNG-CHE 蔡永哲 Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems |
author_sort |
TSAI, YUNG-CHE |
title |
Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems |
title_short |
Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems |
title_full |
Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems |
title_fullStr |
Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems |
title_full_unstemmed |
Jaguar Algorithm with Adaptive Territory for Jumping Mechanism applied to Function Optimization Problems |
title_sort |
jaguar algorithm with adaptive territory for jumping mechanism applied to function optimization problems |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/57421545845830732890 |
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