Research And Application Of Dynamic VRP Based On Quantum Ant Colony Algorithm

With the rapid development of the global economy,people's living standards are constantly improving,and the consequent demand for logistics distribution is also getting higher and higher.Vehicle Routing Problem(VRP)has become a hot topic in the logistics industry in recent years.Vehicle routing problem,as the key link of logistics distribution,is essential to improve the economic benefit of logistics and realize the scientificization of logistics.How to minimize the cost,maximize the efficiency of delivery,and improve the customer satisfaction is gradually becoming the most important issue in the current study of vehicle routing.Vehicle delivery problem is a typical combinatorial optimization problem and NP problem,In recent decades,domestic and foreign scholars have conducted in-depth research on it.The dynamic vehicle routing problem(DVRP)is one of the vehicle routing problem(VRP).Its dynamic and real-time performance is more consistent with the current customer's actual needs.In this paper,the dynamic vehicle routing problem(DVRP)is transformed into a static vehicle routing problem(VRP)by using the two stage modeling method.Considering the degree of customer satisfaction,the fuzzy membership function is introduced.In this paper,we improved the traditional quantum ant colony algorithm and replaced the traditional quantum revolving door with quantum H? gate to update the ant colony.In the dynamic optimization stage,a time period processing method is adopted,and a fuzzy probability formula is introduced to determine whether to insert new customers into the current route or add a new car to deliver new customers.This paper uses MATLAB to carry out the experiment of data simulation,Compared with the other five algorithms,the proposed algorithm is superior to the other five algorithms in terms of algorithm running time,algorithm convergence,and running cost.Experiments show that the improved quantum ant colony algorithm proposed in this paper is an effective method to solve the dynamic vehicle routing problem with uncertain demand of the customers.This paper implements the system function of dynamic vehicle distribution based on quantum ant colony algorithm.The system uses browser/server mode(B/S).based on JavaScript,Baidu map and other technologies.In the system,the system administrator can get the location information of the customer in real time,and input these data as parameters of the algorithm on the server side.Thus,the vehicle distribution route map based on Baidu map is generated.realize the vehicle distribution function of the system.