Research On Optimization Model Of Vehicle Scheduling For Emergency Supplies

The fast and efficient dispatch of emergency supplies and vehicles is an important means to solve public safety events such as sudden natural disasters,accidents,disasters,public health incidents,and social security incidents.It is an effective way to avoid secondary damage caused by disasters,which can minimize the harm caused by public security eventss to human beings and reduce the loss caused by economic development.The development of spatio-temporal intelligence,location intelligence,and optimization technology has made it possible to dispatch emergency supplies with high efficiency and low cost.Therefore,it is of great practical significance to carry out research on optimization model of vehicle scheduling for emergency supplies.Optimization model of vehicle scheduling for emergency supplies is an important issue in the research of emergency logistics of natural disasters.Based on the intelligent optimization algorithms,this disseration has carried out a series of related studies for optimization model of vehicle scheduling for emergency supplies.The research content and innovation of this disseration are as follows1)Aiming at the problem that the emergency vehicle schuduling model for sudden natural disasters does not fully reflect the real distribution of emergency materials,the impact of different road conditions on the speed of the distribution vehicle is analyzed,and an improved emergency vehicle routing problem with relief materials in sudden disasters by using variable speed is proposed.Firstly,the emergency vehicle scheduling problem is abstracted,and a three-layer architecture for emergency vehicle scheduling is given.Secondly,the boundary conditions of variables involved in the model are defined and explained,and the emergency vehicle routing model is designed on this basis.Finally,according to the different speeds of the distribution vehicles under different road conditions,an improved emergency vehicle routing problem with relief materials in sudden disasters by using variable speed is proposed,which is more consistent with the actual vehicle distribution process.2)Aiming at the problem that the emergency material delivery time is too long to meet the actual needs,an enhanced monarch butterfly optimization(EMBO)algorithm is proposed to effectively solve the emergency vehicle routing problems and reduce the emergency material delivery time.Firstly,the characteristics of the basic monarch butterfly optimization(MBO)algorithm are analyzed in depth,that is,the monarch butterfly optimization algorithm shows its unique advantages in benchmark evaluation and other engineering applications,however,sometimes the basic monarch butterfly optimization algorithm may fall into local optimum on some complicated problems.Secondly,combining the adaptive strategy and the crossover operator in evolutionary algorithms with the basic monarch butterfly optimization method,an enhanced monarch butterfly optimization(EMBO)algorithm is proposed.Finally,the proposed EMBO algorithm is discretized and applied to solve emergency vehicle routing problems.Experiments show that the EMBO algorithm is superior to the basic MBO algorithm and other seven intelligent algorithms under the same conditions(artificial bee colony algorithm,bat algorithm,biogeography-based optimization,cuckoo search,differential evolution,evolution strategy,and particle swarm optimization).3)Aiming at the problem of low efficiency of emergency material distribution,a hybrid KHABC algorithm is proposed to solve the problem of emergency vehicle routing problem.Firstly,it deeply analyzes the mechanism,running process and applications of the basic KH and ABC,and the characteristics of the basic KH and ABC algorithms are clarified.Secondly,combining the information sharing and information exchange theory,a new hybrid metaheuristic algorithm namely KHABC is proposed.Finally,an improved natural number coding strategy is used to discretize continuous individuals,so that the basic KHABC algorithm used only for continuous optimization problems is extended to solve emergency vehicle routing problems.The experimental results show that the KHABC algorithm significantly improves the ability of the KH and ABC to solve emergency vehicle routing problems without increasing the computational cost.The optimization performance is significantly better than the other seven comparative algorithms(artificial bee colony,bat algorithm,biogeography-based optimization,cuckoo search,differential evolution,evolution strategy,and particle swarm optimization).4)Aiming at the proposed improved emergency vehicle scheduling model with variable speed,based on the B/S architecture,vehicle scheduling system for emergency supplies was developed.On the server side,the system used the Red Hat Enterprise Linux 7.4 as operating system,My SQL database and PHP 7.4 as parser;on the browser side,Javascript,CSS,and HTML were used.Aiming at the basic model of emergency vehicle scheduling problem,the improved model with variable speed and whether the rescue route is affected by construction,the emergency relief path is intelligently realized.In the vehicle scheduling system for emergency supplies,Amap is used to realize the dynamic display of the material transportation process on the browser side.In summary,the purpose of this dissertation is to solve the practical problems of space-time optimization of vehicle scheduling for emergency supplies by using the theory and method in modern intelligent algorithm,not only enrich and broaden the application field of the theory related to space-time position intelligence algorithm,but also improve the application value of space-time intelligent algorithm,enrich the solution method of optimization model of vehicle scheduling for emergency supplies,and improve the ability of emergency material distribution of public security events.