Research On Route Optimization Of Medical Waste Recovery Vehicle Considering Green Cost

With the continuous improvement of China’s economic level,the overall medical and health level has been developing rapidly,but the amount of medical waste generated continues to rise,especially after the COVID-19 outbreak,the amount of medical waste generated has seen a blowout growth.In the face of the large quantity and wide distribution of medical waste,its timely and effective recovery work faces a severe test.At the same time,in order to realize the comprehensive green transformation of economic and social development,the consideration of green cost in the process of logistics transportation has become an unavoidable problem.In this context,scientific planning of the driving route of medical waste recycling vehicles can reduce the cost and increase the efficiency of the medical waste recycling work considering the green cost,which is of great significance to enterprises and society.In this thesis,the research status of green transportation and medical waste recycling path optimization were elaborated and the research problems were extracted.Secondly,the relevant theories of green logistics,medical waste reverse logistics,clustering algorithm,as well as the basic types and common solving algorithms of path optimization were analyzed.Then,the impact of carbon emissions on the environment was comprehensively quantified,and an optimization model of medical waste recycling path considering green cost was constructed with the goal of minimizing the total cost.At the same time,the location distribution of recovery points and on-board capacity of recovery vehicles were fully considered.The two-stage algorithm of "clustering before distribution" was combined with the actual data to divide the overall large range of recovery areas into several small areas,thus reducing the scale and complexity of route optimization research and laying a foundation for algorithm design.In the design of the algorithm,the basic genetic algorithm is considered first,and the design of the genetic algorithm is described in combination with the total cost minimization objective including green cost.In order to improve the solving speed and quality,the mountain climbing operator was integrated into the genetic algorithm,and the improved genetic algorithm was designed to solve the model,which could not only give play to the global search ability of genetic excellence,but also improve its local search ability.Finally,taking the recovery of medical waste from secondary medical institutions(excluding military hospitals)in Nanjing as an example,the path optimization simulation study was carried out.The problem was solved by MATLAB software,and the results obtained by the improved genetic algorithm of mountain climbing method and the basic genetic algorithm were compared and analyzed.The experimental results showed that the total transportation cost of medical waste recovery was better than that of the basic genetic algorithm based on the vehicle recovery path based on the improved mountain climbing method.On the one hand,the rationality and feasibility of the model and algorithm are verified.On the other hand,the superiority of genetic algorithm improved by mountain climbing method to solve the routing optimization problem of medical waste recovery vehicles considering green cost is demonstrated.At the same time,it also shows that the path planning of medical waste recycling considering green cost can reduce the efficiency through reasonable and scientific planning,so as to achieve the balance between economic benefits and environmental benefits of enterprises.This provides management inspiration and method reference for medical waste recycling enterprises and other waste recycling research.