Pub. online:1 Jan 2018Type:Research ArticleOpen Access
Volume 29, Issue 3 (2018), pp. 499–516
Crossover operators play a very important role by creation of genetic algorithms (GAs) which are applied in various areas of computer science, including combinatorial optimization. In this paper, fifteen genetic crossover procedures are designed and implemented using a modern C# programming language. The computational experiments have been conducted with these operators by solving the famous combinatorial optimization problem – the quadratic assignment problem (QAP). The results of the conducted experiments on the characteristic benchmark instances from the QAP instances library QAPLIB illustrate the relative performance of the examined crossover operations.
All crossover procedures are publicly available with the intention that the GA researchers will choose a procedure which suits the individual demand at the highest degree.