基于改进人工蜂群算法的生鲜农产品配送路径优化

Fresh agricultural product distribution path optimization based on improved artificial bee colony algorithm

为提高生鲜农产品的物流配送效率,降低配送过程中的综合成本,以配送总成本最小化为优化目标,通过引入时间价格成本,结合配送固定成本、运输成本和惩罚成本构建成本函数最小化模型。基于该数学模型,运用改进的人工蜂群算法对模型进行求解,算法中采取中位数选择策略来代替原有的轮盘赌选择策略,并在解的更新阶段引入禁忌表,有效解决了算法容易过早陷入局部最优的问题,并使得算法的收敛速度提高40%。通过算例验证了本文模型和算法的有效性,有一定实践指导意义。

In order to improve the logistics and delivery efficiency of fresh agricultural products and reduce the comprehensive cost in distribution process. In this paper, the objective of minimizing the total cost of delivery is to optimize the cost function by introducing the cost-of-time cost, combining the fixed cost of delivery, transportation cost and penalty cost. Based on the mathematical model, the improved artificial bee colony algorithm is used to solve the model. In the algorithm, the median selection strategy is adopted to replace the original roulette selection strategy, and the taboo list is introduced in the update phase of the solution, which effectively solves the problem that the algorithm is easy to fall prematurely into the local optimal problem and the convergence speed of the algorithm is increased by 40%.The validity of the model and the algorithm in this paper is validated by an example, they are approved to have some practical significance.