An Improvement of Hill Climbing Algorithm with Jumping Strategy

碩士 === 國立金門技術學院 === 電資研究所 === 98 === Hill-Climbing(HC) is an optimization algorithm that is widely known. It’s simple and fast. However, HC will be trapped when it fall into local optima, and cannot find global optimal solution. In this paper, we design a jumping strategy to help HC escape from loca...

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Main Authors: Bo-Yang Lin, 林伯陽
Other Authors: Chung-Chen Chen
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/10690344384197282246
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spelling ndltd-TW-098KMIT07060022016-04-27T04:11:22Z http://ndltd.ncl.edu.tw/handle/10690344384197282246 An Improvement of Hill Climbing Algorithm with Jumping Strategy 採用失敗後跳躍的策略以改良爬山演算法 Bo-Yang Lin 林伯陽 碩士 國立金門技術學院 電資研究所 98 Hill-Climbing(HC) is an optimization algorithm that is widely known. It’s simple and fast. However, HC will be trapped when it fall into local optima, and cannot find global optimal solution. In this paper, we design a jumping strategy to help HC escape from local optima. The new algorithm is called Hill-Climbing with Jumping Strategies(HCJ). This text adopts three popular Nonlinear Programming problems - G1, G7, G9, to test the effect of HCJ algorithm. The result showed that HCJ had excellent performances on G1, G9, but HCJ couldn't work well on G7. Through analyzing the experiment, we realized that G7 may contain a problem itself, this is a problem which HCJ cannot solve at the moment, but it is also an area which HCJ could be improved in the future. However, when comparing HCJ with other single-particle algorithm, such as HC and SA, HC shows much improvement in its accuracy with its performance and solutions; when compared with multi-particle algorithm, we have found out that when HCJ is obtaining a solution, although it is not as good as the modified PSO and GA, but it is better than the original PSO and GA. This is resulted from the modification of the HCJ jumping strategy, it also shows the improvement in the potential of the HCJ jumping strategy. Chung-Chen Chen 陳鍾誠 2010 學位論文 ; thesis 73 zh-TW
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description 碩士 === 國立金門技術學院 === 電資研究所 === 98 === Hill-Climbing(HC) is an optimization algorithm that is widely known. It’s simple and fast. However, HC will be trapped when it fall into local optima, and cannot find global optimal solution. In this paper, we design a jumping strategy to help HC escape from local optima. The new algorithm is called Hill-Climbing with Jumping Strategies(HCJ). This text adopts three popular Nonlinear Programming problems - G1, G7, G9, to test the effect of HCJ algorithm. The result showed that HCJ had excellent performances on G1, G9, but HCJ couldn't work well on G7. Through analyzing the experiment, we realized that G7 may contain a problem itself, this is a problem which HCJ cannot solve at the moment, but it is also an area which HCJ could be improved in the future. However, when comparing HCJ with other single-particle algorithm, such as HC and SA, HC shows much improvement in its accuracy with its performance and solutions; when compared with multi-particle algorithm, we have found out that when HCJ is obtaining a solution, although it is not as good as the modified PSO and GA, but it is better than the original PSO and GA. This is resulted from the modification of the HCJ jumping strategy, it also shows the improvement in the potential of the HCJ jumping strategy.
author2 Chung-Chen Chen
author_facet Chung-Chen Chen
Bo-Yang Lin
林伯陽
author Bo-Yang Lin
林伯陽
spellingShingle Bo-Yang Lin
林伯陽
An Improvement of Hill Climbing Algorithm with Jumping Strategy
author_sort Bo-Yang Lin
title An Improvement of Hill Climbing Algorithm with Jumping Strategy
title_short An Improvement of Hill Climbing Algorithm with Jumping Strategy
title_full An Improvement of Hill Climbing Algorithm with Jumping Strategy
title_fullStr An Improvement of Hill Climbing Algorithm with Jumping Strategy
title_full_unstemmed An Improvement of Hill Climbing Algorithm with Jumping Strategy
title_sort improvement of hill climbing algorithm with jumping strategy
publishDate 2010
url http://ndltd.ncl.edu.tw/handle/10690344384197282246
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