基于动力学的多父体杂交算法

多父体杂交算法将种群中多个个体张成一个空间,然后在此空间中进行空间搜索,该算法具有很强的解搜索能力和较快的运行速度.动力学演化算法根据粒子群的统计物理特性,模拟粒子群在空间中的运动,提出了一种基于统计物理的粒子选择机制.数值实验表明,动力学演化算法是有效的.结合动力学演化算法的选择策略和多父体杂交算法的遗传操作,提出一种新的基于动力学的多父体杂交算法.该算法对多父体杂交算法中的替换策略进行改进,有效地提高了算法的求解能力,数值实验表明新算法可以很好的收敛,能够快速的找到问题的最优解.

Multi-parent Crossover Algorithm Based on Dynamics

Multi-parent Crossover Algorithm selects some individuals to form a space and then do searching in this space.This algorithm has strong ability to find the solutions of the problem,and it also run quickly compared with other traditional algorithms.Dynamical Evolutionary Algorithm based on Statistical Mechanics simulates the movement of the particles in space.A new select mechanism was proposed in it.The numerical experiments show that Dynamical Evolutionary Algorithm is effective.A new Multi-parent Crossover Algorithm based on Dynamics unites the select mechanism of the Dynamical Evolutionary Algorithm with the evolutionary operations of Multi-parent Crossover was proposed.The algorithm also changed the replace strategy of the Multi-parent Crossover,and this change improved the algorithm's searching ability.Numerical experiments show that the convergence of the new algorithm is good,and the optimal solution can be found within a shorter period of time by using this new algorithm.