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초록
영어
The traveling salesman problem (TSP) is one of the most studied in operations research and computer science. Research has led to a large number of techniques to solve this problem; in particular, genetic algorithms (GA) produce good results compared to other techniques. A disadvantage of GA, though, is that they easily become trapped in the local minima. In this paper, a cuckoo search optimizer (CS) is used along with a GA in order to avoid the local minima problem and to benefit from the advantages of both types of algorithms. A 2-opt operation was added to the algorithm to improve the results. The suggested algorithm was applied to multiple sequence alignment and compared with the previous algorithms.
목차
Abstract
1. Introduction
2. Metaheuristic Algorithms
2.1. Cuckoo Search Algorithm (CS)
2.2. Genetic Algorithm (GA)
2.3. Simulated Annealing(SA)
2.4. Ant Colony Optimization Algorithm
3. A Hybrid Algorithm for TSP
4. Experimental Results
5. TSP for Multiple Sequence Alignment
6. Conclusion
References
1. Introduction
2. Metaheuristic Algorithms
2.1. Cuckoo Search Algorithm (CS)
2.2. Genetic Algorithm (GA)
2.3. Simulated Annealing(SA)
2.4. Ant Colony Optimization Algorithm
3. A Hybrid Algorithm for TSP
4. Experimental Results
5. TSP for Multiple Sequence Alignment
6. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보