基于改进遗传算法的渔港规划问题研究

为解决渔港规划的选址问题，基于所有渔船和渔港总距离和最优构建该问题的数学模型，提出一种改进的遗传算法的求解方法。给出适用于该问题的基因和染色体的定义；设计适应度函数，并根据适应值均匀分布对初始种群进行优化，提高种群的多样性；给出个体相似性的定义，由相似度函数和种群方差决定个体的配对方式；在满足基因排他性的条件下，根据交叉和变异概率进行交叉和变异操作。实验表明，该算法可以有效、准确地求得大规模数据的渔港规划问题的全局最优解。

Research of fishing port planning problem based on improved genetic algorithm

To solve the fishing port planning location problem, a mathematics model has been made on the ba-sis of the optimization of total sum of distance between all fishing vessels and ports. An optimization solution based on an improved Genetic Algorithm(GA) has been proposed. Definition of gene and chromosome suits to the problem are given. Fitness function is designed, and then initial population is optimized by fitness function valuses uniform distribution, so as to improve diversity of population. Definition of individuality similarity is given, and then mate pattern lied on similarity function and population variance. According to cross and muta-tion probability, cross and mutation operations are progressed under the condition of gene rejection.The result from the experiments shows that the global optimal solution of the problem is efficient and accurate resolved by the improved algorithm.