【摘要】 针对物流仓库的拣货-复核路径规划问题，首先利用货格所在行列的奇偶性，根据曼哈顿距离公式，建立了仓库内任意两拣货点(含复核台)之间的距离计算公式。然后将整个拣货-复核作业过程映射为一个旅行商问题，构建了0-1规划模型。最后选用小生境遗传算法进行求解，在变异策略中引入小生境技术，保证了种群的多样性，较好地克服了标准遗传算法中种群早熟和易陷入局部最优的缺点。实验仿真选取1个复核台和有15,30,45,60个拣货点的4种情形，与标准遗传算法相比，该算法求得的最优路径长度可以明显缩短，且收敛速度更快、稳定性更好，尤其拣货点数越多时路径优化效果越明显。更多还原

【Abstract】 In order to solve the problem of picking-review path planning in logistics warehouse, firstly,according to Manhattan distance formula, the calculation formula of the distance between any two picking points(including the review table) in the warehouse is established by using the parity of the row and column of the goods lattice. Then, the whole picking review process is mapped to a traveling salesman problem, and the 0-1 programming model is constructed. Finally, niche genetic algorithm is used to solve the problem, and niche technology is introduced into the mutation strategy to ensure the diversity of the population, which overcomes the shortcomings of premature population and easy to fall into local optimum in the standard genetic algorithm.The experimental simulation selects four cases with one review table and 15, 30, 45, 60 picking points, compared with the standard genetic algorithm, the optimal path length obtained by the algorithm can be reduced obviously,and the convergence speed is faster and the stability is better, especially when the number of picking points is more.更多还原