THE TERMINATION OF THE UNCERTAINTY OF GENETIC ALGORITHM

Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. Put Abstract text here. At present, the genetic algorithm has always taken the optimization of generation, the approximate distance and the time constraints by the end of optimization as the termination conditions. The approximate value has the uncertain characteristic when the algorithm is finished, which can't meet the approximate demands in practical application. According to the uncertain needs of measurement, it is necessary to consider the measurement of uncertainty as the termination condition of genetic algorithm in the process of evaluation measurement. We should employ the important model for evaluation in the realization of algorithm. It is required to use the short important model to accumulate the long high-order model. When the blocks model meets the requirements of uncertainty, the algorithm will be finished.