Research On Multi-objective Cold Chain Logistics Path Planning With Uncertain Time Window

It can be seen from the opinions on accelerating the development of cold chain logistics to ensure food safety and promote consumption upgrading issued by the State Council in 2017 that in order to plan the infrastructure construction of cold chain logistics as a whole,establish the infrastructure network covering all parts of the country,promote the scientific development of the industry,and ensure the food safety of the people,the industry short board of "last kilometer" must be supplemented.In this context,the master thesis starts from the "last kilometer" first,and after a large number of literature review,it is found that most of the previous studies focus on the deterministic factors,and the research on the uncertain factors,especially the time window,is still very insufficient,so the master thesis takes the multiobjective cold chain logistics decision with uncertain time window as the research direction.Then,starting from the basic vehicle routing optimization model,and according to the characteristics of the cold chain logistics products in transit,which are easy to damage,need refrigeration,high time efficiency requirements,and carbon emission indicators,the basic assumptions are put forward.The hypothesis of time window is explained in detail,and customer satisfaction is described by time window function.In this master thesis,cold chain logistics theory,vehicle routing optimization,ant colony algorithm theory is combined to build a cold chain logistics optimization model with uncertain time window,with the shortest distance,the lowest cost and the highest customer satisfaction as the optimization goals.Finally,data acquisition and processing are carried out,parameters are set,and a certain number of time window data groups with a time window length longer than or equal to 1 hour are randomly generated,and the time window data group with the smallest total path obtained by solving the model through ant colony algorithm is selected,and then the minimum interval length of this group of time window data is reduced to 0.5 hours to achieve the minimum time window length In the case of small-scale distribution,time window is an extremely important factor.Among 100 randomly generated time windows with minimum interval length ≥ 60,the shortest distance and the longest data are selected to compare with the shortest distance.In addition,the master thesis also considers Some typical cases without solutions are analyzed and discussed.The model can not only provide theoretical basis for the cold chain logistics industry related issues and services,but also expand the application of ant colony algorithm to the optimization of complex data sets,which is also a supplement to the cold chain logistics optimization theory and other related theories.