针对商超配送中多种配送方式共同面临的车辆配载和路径规划问题, 考虑配送车辆容量限制, 以最小化配送总成本为目标, 构建了基于订单拆分的带容量限制商超配送路径规划模型. 结合真实案例, 提出了一种增加遗传变异操作的改进灰狼优化算法. 通过与遗传算法的对比, 验证了模型和算法的有效性. 案例分析结果表明, 当总商超客户需求量接近车辆容量的整数倍时, 基于订单拆分配送路径规划更能够充分地利用车容量, 降低车辆的空驶率, 减少配送总成本.

Vehicle stowage and route planning are common problems for various delivery methods related to supermarket distribution. In order to resolve these problems, we propose capacitated route planning for supermarket order distribution based on order splitting. We construct the problem model with the goal of minimizing the total cost of delivery. Combined with real cases, an improved gray wolf optimization algorithm adding a genetic mutation operation is proposed. The effectiveness of the model and algorithm is verified by comparing performance with the genetic algorithm. The results show that when the total demand of supermarkets is close to an integer multiple of the vehicle capacity, our proposed planning approach is better. This is mainly reflected in the fact that the order splitting plan can make full use of vehicle capacity, reduce the empty driving rate for vehicles, and reduce the total distribution cost.