Good Point Set Genetic Algorithm with Zooming Factor
变焦佳点集遗传算法

Good point set genetic algorithm has superiority in convergence speed, accuracy and overcome premature effectively by using the good point operator which is based on the principle of set in number theory. However, when the length of chromosome is fixed, the discretization error is inevitable. Aiming at the domino phenomenon of convergence from the highest position to lowest position of binary coding in good point set genetic algorithm, a zooming factor was proposed to lengthen the length of chromosome indirectly to minimize the discretization error, so the search efficiency and solution accuracy are improved as a result hhe simulation results based on Benchmark test function of different dimensions verify that the proposed good point set algorithm with zooming factor has the advantage of global convergence, high precision solution and search efficiency.