Abstract
This paper addresses an application of genetic algorithms (GA) for solving the travelling salesman problem (TSP), it compares the results of implementing two different types of two-point (1 order) genes crossover, the static and the dynamic approaches, which are used to produce new offspring. By changing three factors; the number of cities, the number of generations and the population size, the goal is to show which approach is better in terms of finding the optimal solution (the shortest path) in as short time as possible as a result of these changes. Besides, it will explore the effect of changing the above factors on finding the optimal solution.
| Original language | English |
|---|---|
| Pages (from-to) | 209-213 |
| Number of pages | 5 |
| Journal | International Journal of Information Technology |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Mar 2020 |
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Cite this
Alqura'N Alzyadat, T., Yamin, M., & Chetty, G. (2020). Genetic algorithms for the travelling salesman problem: a crossover comparison. International Journal of Information Technology , 12(1), 209-213. https://doi.org/10.1007/s41870-019-00377-9