研究生: |
陳一帆 Subrata, - Evan |
---|---|
論文名稱: |
Hybrid Model of RSSA and Modified Grover Algorithm in Optimizing Tower Crane Location Hybrid Model of RSSA and Modified Grover Algorithm in Optimizing Tower Crane Location |
指導教授: |
呂守陞
Sou-Sen Leu |
口試委員: |
林建良
none 楊亦東 I-Tung Yang |
學位類別: |
碩士 Master |
系所名稱: |
工程學院 - 營建工程系 Department of Civil and Construction Engineering |
論文出版年: | 2009 |
畢業學年度: | 97 |
語文別: | 英文 |
論文頁數: | 170 |
外文關鍵詞: | Grover Algorithm, RSSA, Searching Algorithm |
相關次數: | 點閱:240 下載:9 |
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This thesis presents a hybrid model of a new and adopted searching algorithm from Computer Science, named Grover Algorithm with one of new established meta-heuristic algorithm, RSSA (Reduced Space Searching Algorithm). Since Grover Algorithm has to be applied in a quantum computer system which is not available at this moment, only the basic concept will be occupied, that makes it more related to enumeration. As a meta- heuristic algorithm whose basic concept is adopted from reducing search space strategy, RSSA will greatly reduce the original search space and delivers the remaining search space to Grover Algorithm to find the best solution. The combination of both algorithms is validated by solving multiple peak functions. The traditional Genetic Algorithm (GA) is used as a standard of comparison in appraising the RSSA-Grover result. Simulation result shows that RSSA-Grover performed better than GA due to its accuracy. Furthermore, this proposed algorithm is successfully applied to solve the real case of Tower Crane location selection, whose objective is to find the minimum duration due to cost minimizing, concealed by abundant constraints and decision variables.
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