基于免疫克隆算法的物流配送车辆路径优化研究

物流配送车辆路径优化问题是近年来物流领域中的研究热点，该问题属于NP难题，较难得到最优解和满意解．在物流配送车辆路径优化问题数学模型的基础上，构造了一种免疫克隆算法来求解该问题，并在算法中引入了克隆选择、克隆删除、受体编辑、体细胞高频变异、抗体循环补充等思想．仿真计算结果表明，免疫克隆算法能快速收敛于全局最优解，克服了遗传算法中易陷入局部最优解和收敛速度慢的缺点，可有效地解决物流配送车辆路径优化问题．

Study on the Optimization of Logistics Distribution VRP Based on Immune Clone Algorithm

The logistics distribution VRP is a hot topic in logistics research. It is a NP problem and hard to get an optimal and satisfactory solution. On the basis of the mathematic model for Logistics Distribution VRP, this paper presented an Immune Clone Algorithm (ICA) to solve this problem. The concepts of clonal selection, clonal deletion, receptor editing, somatic hypermutation and antibody supplement were introduced. Experimental calculation results showed that ICA could converge to global optimal solution rapidly and solve the logistics distribution VRP effectively. It can avoid the convergence to the local optimal solution and overcome the slow convergence velocity of the Genetic Algorithm.