A High-Performance Genetic Algorithm: Using Traveling Salesman Problem as a Case

Autor: Chun-Wei Tsai, Shih-Pang Tseng, Ming-Chao Chiang, Chu-Sing Yang, Tzung-Pei Hong
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Zdroj: The Scientific World Journal, Vol 2014 (2014)
Druh dokumentu: article
ISSN: 2356-6140
1537-744X
DOI: 10.1155/2014/178621
Popis: This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA.
Databáze: Directory of Open Access Journals
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