http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Rung-Ching (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Solving Unbounded Knapsack Problem Using an Adaptive Genetic Algorithm with Elitism Strategy
Rung-Ching Chen,Cheng-Huei Jian,Yung-Fa Huang 보안공학연구지원센터 2008 International Journal of Smart Home Vol.2 No.2
With the popularity of sensor networks, solving the knapsack problem has become important in selecting the best combination of sensor nodes. Many methods have been proposed to solve the Knapsack problem, but few of them have used the genetic algorithm, especially in unbounded Knapsack problems. In this paper, we use the genetic algorithm to solve the unbounded Knapsack problem. We combine an elite strategy and a self adapting system into the genetic algorithm. Using the elite strategy overcomes the problem of the slow convergence rate of the general genetic algorithm. The elite strategy retains good chromosomes and ensures that they are not eliminated through the mechanism of crossover and mutation, ensuring that the features of the offspring chromosomes are at least as good as their parents. The system automatically adapts the number of the initial population of chromosomes and the number of runs to be executed in the genetic algorithm. It will obtain the best value from the chromosomes of each run executed, and retain the values in an elite group. The optimal value is then taken from the elite group and adopted as the real solution. Experimental results have shown that our method rapidly discovers the best solution of the problem.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
