| The optimization of DNA encodings based on GA/SA algorithms |
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| 引用本文： | Wang Wei1,Zheng Xuedong2,Zhang Qiang1 and Xu Jin2(1. Liaoning Key Laboratory of Intelligent Information Processing,Dalian University,Dalian 116622,China, 2. Department of Control Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China). The optimization of DNA encodings based on GA/SA algorithms[J]. 自然科学进展(英文版), 2007, 17(6): 739-744 |
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| 作者姓名： | Wang Wei1 Zheng Xuedong2 Zhang Qiang1 and Xu Jin2(1. Liaoning Key Laboratory of Intelligent Information Processing Dalian University Dalian 116622 China 2. Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China) |
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| 作者单位： | 1. Liaoning Key Laboratory of Intelligent Information Processing，Dalian University，Dalian 116622，China; 2. Department of Control Science and Engineering，Huazhong University of Science and Technology，Wuhan 430074，China |
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| 基金项目： | 国家自然科学基金;教育部高校新世纪杰出人才项目 |
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| 摘 要： | The design of DNA sequence plays an important role in improving the reliability of DNA computation. Proper constrained terms that DNA sequence should satisfy are selected, and then the evaluation formulas of each DNA individual corresponding to the selected constrained terms are proposed. The heuristic improved genetic algorithm (GA)/simulated annealing (SA) algorithm is presented to solve the multi-objective optimize problem, and the DNA sequence design system is developed. Furthermore, an example is illustrated to show the efficiency of our method given here.
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The optimization of DNA encodings based on GA/SA algorithms |
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| Wang Wei,Zheng Xuedong,Zhang Qiang,Xu Jin. The optimization of DNA encodings based on GA/SA algorithms[J]. Progress in Natural Science, 2007, 17(6): 739-744 |
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| Authors: | Wang Wei Zheng Xuedong Zhang Qiang Xu Jin |
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| Abstract: | The design of DNA sequence plays an important role in improving the reliability of DNA computation. Proper constrained terms that DNA sequence should satisfy are selected, and then the evaluation formulas of each DNA individual corresponding to the selected constrained terms are proposed. The heuristic improved genetic algorithm (GA)/simulated annealing (SA) algorithm is presented to solve the multi-objective optimize problem, and the DNA sequence design system is developed. Furthermore, an example is illustrated to show the efficiency of our method given here. |
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| Keywords: | DNA encoding multi-objective optimize GA/SA algorithms |
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