Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6904522 | Applied Soft Computing | 2016 | 9 Pages |
Abstract
The paper provides a multi-offspring genetic algorithm (MO-GA) in accordance with biological evolutionary and mathematical ecological theory, and illustrates its application in the traveling salesman problem (TSP) in comparison to the basic genetic algorithm (BGA). In MO-GA, the number of offsprings is significantly increased as compared to the BGA. MO-GA increases the probability of producing excellent individuals, and also makes the population more competitive, thus yielding considerable improvement. Test results with six TSP examples show that MO-GA has faster speed, and the number and time of iterations are significantly reduced as compared to the BGA.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Jiquan Wang, Okan K. Ersoy, Mengying He, Fulin Wang,