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为解决物流配送车辆路径优化问题,给出了一种基于免疫计算的车辆路径优化方案,设计了车辆路径问题的数学模型,给出了非劣邻域支配的多目标免疫优化算法的框架、基于实数编码的比例克隆算子和领域变异算子以及支配抗体的拥挤距离公式,并在仿真环境下进行了实验;结果表明,算法能使多目标优化问题收敛到Pareto最优解集,并在Pareto曲线上有均匀的分布,具有较好的应用价值。
In order to solve the problem of vehicle routing optimization in logistics and distribution, a vehicle routing optimization scheme based on immune calculation is presented. The mathematical model of vehicle routing problem is designed. The framework of multi-objective immune optimization algorithm which is dominated by non-inferior neighborhood is given. Real number encoding ratio cloning operator and field mutation operator and the governing distance of crowding distance antibody were simulated experimentally. The results show that the algorithm can make the multi-objective optimization problem converge to the Pareto optimal solution set, and in Pareto The curve has a uniform distribution, with good application value.