Distribution path optimization based on dynamic hybrid genetic algorithm
With the outbreak of more and more sudden health events,people's demand for emergency medical supplies is increasing,but the problems such as inefficient distribution of emergency medical supplies still exist.This paper considers the establishment of a multi-distribution point distribution model,which effectively optimizes the distribution path from multiple emergency medical materials distribution centers to multiple distribution points,and considers the customer time window and traffic congestion in the calculation process,so as to achieve the goals of improving customer satisfaction,saving costs and reducing carbon emissions generated in the distribution process.The dynamic hybrid genetic algorithm(DHGA)is used in the calculation process of the model,and the large-scale domain search algorithm is added to the improved genetic algorithm to solve the shortcomings of the genetic algorithm that the accuracy is too low and it is easy to fall into the local optimal cycle.Finally,the results are compared with the traditional genetic algorithm(GA),particle swarm optimization(ACO)and ant colony algorithm(ACO),and the final results show that the algorithm has improved significantly in various indexes compared with other algorithms.
emergency medical treatmentdynamic hybrid genetic algorithmpath optimizationcarbon emissionsVRP
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