원문정보
보안공학연구지원센터(IJGDC)
International Journal of Grid and Distributed Computing
Vol.8 No.3
2015.06
pp.359-370
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper presents a hybrid algorithm for traveling salesman problem. The algorithm is a combination of the genetic algorithm and simulated annealing algorithm; in other words, it is a hybrid algorithm. The combination overcomes the deficiencies of the two algorithms when acting separately. The real distance between customers has been used on the basis of geographical information system (GIS) in order to make the result more suitable in real-life. The algorithm has tested on the examples of international standards. We made a comparison with the result of second nearest neighbor algorithm and genetic optimization algorithm. The test showed that the algorithm proposed in this paper has improved the results.
목차
Abstract
1. Introduction
2. GIS in Logistics and Distribution
3. Model Based on GIS
4. Algorithm
4.1. The Basic Idea of the Hybrid Algorithm
4.2. The Key Points of Genetic Algorithm
4.3. The Key Step of Simulated Annealing Algorithm
4.4. Steps of Hybrid Algorithm Implementation
4.5. Computational Comparison
5. Conclusions
6. Acknowledgements
References
1. Introduction
2. GIS in Logistics and Distribution
3. Model Based on GIS
4. Algorithm
4.1. The Basic Idea of the Hybrid Algorithm
4.2. The Key Points of Genetic Algorithm
4.3. The Key Step of Simulated Annealing Algorithm
4.4. Steps of Hybrid Algorithm Implementation
4.5. Computational Comparison
5. Conclusions
6. Acknowledgements
References
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자료제공 : 네이버학술정보