Earticle

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

키워드

저자

• Ala'a Abu-Srhan [ Faculty of Science and Information Technology Zarqa University, Zarqa, Jordan ]
• Essam Al Daoud [ Faculty of Science and Information Technology Zarqa University, Zarqa, Jordan ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605