The Traveling Salesman Problem as a Benchmark Test for a Social-Based Genetic Algorithm
N. A. AL-Madi & A. T. Khader
Journal of Computer Science, Volume 4, Issue 10, pp. 871–876 · doi.org/10.3844/jcssp.2008.871.876
Abstract
Present research, showed Traveling Salesman Problem (TSP) to compare values and results concerning the averages and best fits of both, Simple Standard Genetic Algorithm (SGA) and a new approach of Genetic Algorithms named Social-Based Genetic Algorithm (SBGA). Results from TSP test on Social-Based Genetic Algorithms (SBGA) were presented. Results were encouraging in Social-Based Genetic Algorithms (SBGA) performs better in finding best fit solutions of generations in different populations than the Simple Standard Genetic Algorithm.
Licence and reuse
Free to read. This article carries the publisher’s copyright, as printed on it: © 2008 Science Publications. It is free to read; ask us before reusing it.
How to reuse this articleResponses (0)
About this article
AL-Madi, N. A. & Khader, A. T. (2008). The Traveling Salesman Problem as a Benchmark Test for a Social-Based Genetic Algorithm. Journal of Computer Science, 4(10), 871–876. https://doi.org/10.3844/jcssp.2008.871.876
- Licence
- © Science Publications
- Issue
- Volume 4, Issue 10
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
