Study On Vehicle Scheduling Problem And Algorithm Based On Cloud Distribution Model

With the rapid development of the world's economic and progress of modern science and technology, as an important national service industry, the logistics industry is developing rapidly worldwide, and has become the basic industries and development artery of the national economy. Its level of development has become an important indicator of a country's modernization level and overall national strength. However, the logistics researches also stay in the traditional distribution model. With the rapid development of e-commerce and chain stores, logistics distribution model has changed dramatically, appears joint distribution, dynamic distribution, cross-regional large-scale distribution and so new distribution demand, making the traditional logistics model has been difficult to support the needs of modern logistics distribution. Especially the emergence of communication technology and cloud computing, making large-scale cross-regional joint distribution as possible, the new logistics model will be born.Logistics distribution is the key to optimize the modern logistics services supply chain, is also essential support part to expanding modern e-commerce activities. The research of vehicle scheduling problem of logistics distribution is the foundation of developing intelligent transport systems, building integrated logistics systems and expanding e-commerce. Through nearly fifty years'development and study, vehicle scheduling problem has become research hot and cutting-edge topics of operations research and combinatorial optimization field. In realistic production and life, postal delivery problems, flight arrangements, railway vehicles marshalling, terminals transporting, shipping vessels transporting, bus scheduling, power scheduling problem and so can be abstracted for the vehicle scheduling problem. With the development of e-commerce, Internet and communication technology, logistics distribution and vehicle scheduling problem have a wide range of application prospect in the field of chain stores, shopping centers, express and so on. Therefore, the in-depth study of vehicle scheduling problem has high scientific significance and value in engineering.Research contents and innovations of this thesis are as follows:①The cloud distribution model was proposed combining with the relationship between cloud computing model and social logistics distribution.The meaning of cloud computing, development status and application were analyzed, the cloud distribution model was proposed combining with similar characteristics and contraction between cloud computing model and social logistics distribution, the characteristics of cloud distribution patterns and differences and similarities with the traditional logistics model were analyzed. The relationship and action mechanism of distribution resources, delivery cloud services and distribution cloud were analyzed, community-oriented distribution of the "public cloud" service platform was built, and the key technology to building platform was analyzed.②The vehicle scheduling problem with fixed demands under the cloud distribution mode was studied.By having a research on the vehicle scheduling problem with fixed demands under the cloud distribution mode, a mathematical model of vehicle scheduling problem faced with mileage constraint, heavy constraint and time window constraint was established. Based on analysis and comparison the solving algorithms of vehicle scheduling problem, a improved genetic algorithm for solving the vehicle scheduling problem under multi-constraints was proposed, natural number coding genetic algorithm for vehicle scheduling problem was designed to improve the traditional crossover-mutation operation mode, and population expansion mechanism was designed to strengthen the rapid optimization and the global convergence ability. Experimental was combined to test the model and the effectiveness of the algorithm, and the solving results of vehicle scheduling problem with different constraints was contrasted.③The vehicle scheduling problem with dynamic demands under the cloud distribution mode was studied.By proposing the concept of timeline, a research on the vehicle scheduling problem with dynamic demands under the cloud distribution mode was conducted. Timeline and dynamic information driven mechanism was adopted to record the distribution network information, This transforms dynamic vehicle scheduling problem into a series of static vehicle scheduling problems, considering constraint conditions and objective function that more close to the reality, vehicle scheduling model for specific time was established. As vehicle scheduling problem has a high demand in time-sensitive, in this thesis, a method by using quantum theory to improve traditional genetic algorithm was put forwards, designed quantum genetic algorithm, the diversity characteristic of qubits was used to design chromosome coding, and the mechanism of quantum gate spin was adopted to improve the efficiency of the population evolution. Combined with vehicle scheduling model, a"Initial+Real-time"two-stage solution algorithm was design, when requirements proposed by the dynamic demand customer, timeline was used to mark different moments and update the information in the distribution network, then for real-time optimization. Combined with the experimental, simulation computation was used to the designed algorithm to verify the validity of the model and algorithm.④The vehicle scheduling problem of joint distribution under the model of the clouds of distribution was studied.By having an analysis on the key factors of interregional joint distribution under the model of clouds of distribution , the method to solve the Multi Vehicles, multi-distribution centers, open and dynamic vehicle scheduling problem was put forward in this thesis,and according to the timeline concept, a joint distribution of dynamic vehicle scheduling model was build. By using quantum theory and cloud model theory, genetic algorithm was improved, the genetic algorithm chromosome structure was designed by adopting the quantum bits , according to quantum gate rotating population evolution was realized, cloud droplets stability and tendentiousness characteristics of the cloud droplet of cloud model was used to improve the set mode of crossover probability and mutation probability, cloud quantum genetic algorithm was designed and the performance parameters, convergence and computing complexity of the algorithm was analyzed. The designed algorithm and model were got analyzed combined with experiment.⑤The design and implementation of intelligent vehicle scheduling system were studied.According to the complexity and dynamic nature under the model of the cloud distribution, object-oriented vehicles dispatch system was designed. By developing an analysis on principles of system development and requirements of the distributing task under the model of the clouds distribution, a frame structure of open intelligent vehicle scheduling system was build. Through analyzing function module of the system, the business process and operation model of this system was proposed and intelligent vehicle scheduling system of the interface and function modules were on display.Finally, there is a summary on the studies of the whole thesis, the study prospect of operation mechanism of cloud distribution mode, as well as vehicle scheduling problem and its solving algorithm was given.