TESTING OF CROSSOVER OPERATORS FOR THE GREY PATTERN PROBLEM
研究了遗传算法中不同交叉算子对灰色模式问题求解性能的影响，通过实验比较七种算子，发现多父本交叉效率较高。
Recently genetic algorithms (GAs) are a great success in solving combinatorial optimization problems. In this paper the performance issues related to the genetic search in the context of the grey pattern problem (GPP) are discussed. The main attention is paid to the investigation of the solution recombination, i.e. crossover operators, which play an important role developing robust genetic algorithms. We implemented seven crossover operators within the hybrid genetic algorithm (HGA) framework, and carried out the extensive experiments in order to test the influence of the recombination operators on the genetic search process. The results obtained from the experimentation with GPP test instances (benchmarks) demonstrate promising efficiency of so‐called multiple parent crossover which is based on a special type of recombination of several solutions‐parents.