Genetic algorithm-based medical material distribution path optimization research
基于遗传算法的医疗物资配送路径优化研究

摘要

医疗物资的分配是一个典型的优化问题。本文以山西国药集团医药物流订单数据为基础，对医药物资配送相关问题进行建模研究。建立改进的遗传算法模型，对医疗耗材配送路线方案进行数学建模，以“物资供应重量、医疗供应点”为决策变量和约束条件，确定“运输车辆可以跨越所有地点，成本最低”。并对“医疗物资配送路线”进行编码，利用遗传算法对医疗物资配送路线进行优化。最后，计算出“运输车辆能以最低成本遍历所有地点”的最优解。在以上分析的基础上，我们就医疗物资的配送向公司提出了自己的建议，可用于更复杂的环境路径规划问题。

Abstract

The distribution of medical supplies is a typical optimization problem. In this paper, we model and study the problems related to the distribution of medical supplies based on the pharmaceutical logistics order data of Shanxi Sinopharm Group. An improved genetic algorithm model is developed to mathematically model the medical supplies distribution route scheme, with "weight of supplies and medical supply points" as the decision variables and constraints, and to determine "the lowest cost for transport vehicles across all locations". The "medical supply route" is coded and the medical supply route is optimised using a genetic algorithm. Finally, the optimal solution of "the transport vehicle can traverse all locations at the lowest cost" is calculated. Based on this analysis, we make recommendations to the company regarding the distribution of medical supplies. Finally, an optimal solution is calculated for "the transport vehicle that can travel to all locations at the lowest cost". Based on the above analysis, we have made our own recommendations to companies for the distribution of medical supplies, which can be used for more complex environmental route planning problems.