Research On Road Optimization In The Context Of COVID-19

A novel coronavirus(COVID-19),which firstly emerged in 2019 and massively indiscriminately attacks people around the world in 2020,has a huge and irreversible impact on the global economy and on the lives of people across nations.Since the new crown epidemic is sudden and asymptomatic,some of the previous research data also failed in their entirety,and many of the problems were transformed from the original traditional deterministic problems to the non-deterministic problems,and the research networks also changed from the original deterministic networks to the non-deterministic ones,so that the research on some of the classical optimization problems under the network with many non-deterministic factors also became hot issues studied by various expert scholars.Among all the network optimization problems,the path optimization problem continues to be the significant branches of the classic and a large-scope practical application,using knowledge such as graph theory to model the route optimization problem,combining widely applied computer technology to propose some more efficient intelligent algorithms,also become the research goal of many scholars.In the common efforts of expert scholars from various countries around the world,the research on the path optimization problems has also made a great deal of progress,and various types of path optimization problems have been studied and discussed,and according to different real-world situations,many intelligent algorithms have also been applied so efficiently,for solving various distinct path planning problems,from which it can be seen that the research on the path optimization problems is increasingly close to the reality situation,which provides affordable support for the development of real society and the promotion of work productivity.For the sake of better fitting the real-world situation,and based on the research large background of new crown outbreaks-the missing background of data caused by various sudden situations,there are a great numbers of issues in the real-world that cannot generate the probability distribution function by fitting a large number of statistics,at which point the real-world situation becomes an environment where random factors coexist with uncertain factors,on account of the above-mentioned state of affairs,also to complement various models of the essential path optimization problems,the work that this article will do is summarized as follows:Based on the actual background of COVID-19,using the tool of chance theory that can be used to deal with the uncertain parameters present in a network,this paper will discuss two classical path optimization problems based on a network of uncertain stochastic nature coexisting with uncertainty:the uncertain random(UR)shortest path problem(SPP),the UR resource constrained SPP(URRCSPP),and the uncertain identification of random travelling salesman problems(URTSP)in the context of the new crown epidemic.Apart from the novelty of the research context,this paper innovatively applies the newly defined cross entropy to deal with the URSPP,builds a new cross entropy optimization model and varies this model,builds a resource constrained path optimization model,and simultaneously studies the TSP under the COVID-19,i.e.in the uncertain random network(UR-Network)context,proposing three different models:the uncertain random expected value TSP model(UREVTSP),?-URTSP,and uncertain random maximum measure TSP(URMCMTSP)model.