基于离散海鸥算法求解循环取货车辆路径问题

Solving Vehicle Routing Problem of Milk-Run Based on Discrete Seagull Algorithm

针对如何降低循环取货车辆路径问题(VRP:Vehicle Routing Problem)中的运输成本,提出一种离散海鸥算法。首先,在海鸥迁移过程中,采用insert、 reverse操作更新海鸥位置加快算法寻优速度;其次,在海鸥攻击过程中,采用swap、 3-opt操作更新海鸥位置提升算法局部搜索能力;最后,结合模拟退火算法避免算法在运行过程中陷入局部最优,重新定义了在离散的车辆路径问题下的更新策略。以总成本最低为目标函数,构建相应的数学模型。实验结果表明,该算法具有高效解决循环取货车辆路径问题的能力,寻优效果及求解质量均高于标准海鸥优化算法、粒子群算法、模拟退火算法、灰狼优化算法、鲸鱼算法和飞蛾扑火算法。

To reduce the transportation cost in the VRP(Vehicle Routing Problem)of milk-run,a discrete seagull algorithm is proposed.Firstly,in the process of seagull migration,insert and reverse operations are used to update the seagull position to improve the algorithm's search speed.Secondly,swap and 3-opt operations are used to update the seagull position to improve the algorithm's local search capability.Finally,combined with simulated annealing algorithm,the phenomenon of landing on local optimum is prevented during the operation of the algorithm,the update strategy is redefined under the discrete vehicle routing problem.With the lowest total cost as the objective function,the corresponding mathematical model is constructed.Experiment results show that the algorithm is able to efficaciously deal with the vehicle routing problem of milk-run,the finding effect and solution quality are better than the standard seagull optimization algorithm,particle swarm algorithm,simulated annealing,gray wolf optimization,whale optimization algorithm,and moth-flame optimization.