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1、物流配送車輛優(yōu)化調(diào)度問題的探討(Discussion on optimal scheduling of logistics delivery vehicles)Discussion on optimal scheduling of logistics delivery vehiclesAbstract: with the continuous development of economy, the city is changing with each passing day. The development of the city can not be separated from the u

2、se of a large number of trucks, so how to solve the problem of optimal scheduling of logistics delivery vehicles has gradually become the focus of urban construction and development. Logistics distribution vehicle scheduling problem, namely the fixed loading (unloading) goods location, route choice

3、is more appropriate for the vehicle in order from all road points, and also played a certain role in optimization in task in accordance with the requirements of the situation. This paper begins from in-depth overview and the process of logistics distribution, classification and optimization algorith

4、m for optimization problem of vehicle scheduling of logistics distribution in detail, but also further analyzes the development direction of domestic and international logistics vehicle scheduling optimization research status and future.1 logistics distribution overview and process1.1, logistics and

5、 distribution of the basic overviewThe delivery of the intended goods from the consignor to the consignee is called delivery. As the ultimate goal of distribution is the consignee, that is, consumers, therefore, distribution is also a critical step in the logistics system. The distribution is not li

6、mited to the distribution and delivery. To meet the needs of customers, distribution needs to meet the customer on the basis of the type and quantity of the goods, and on the basis of ensuring on-time delivery of customers, select the faster and more cost saving distribution program to maximize the

7、benefits.1.2 optimization of logistics distribution systemIn order to find an optimal logistics distribution plan, we should start from the following aspects: Dispatching of distribution vehicles, selection of the collection line, selection of delivery routes, and integration of goods delivery and d

8、elivery. Optimization of distribution system can not only increase the economic benefits of logistics, more conducive to the realization of scientific, modern logistics management, improve logistics service quality, improve the logistics companys reputation, so as to effectively reduce logistics cos

9、ts.1.3 logistics distribution processWith the development of logistics, modern logistics distribution level, goods circulation is greatly enhanced, the role of traditional storage areas is gradually declining, also makes the distribution to replace the storage areas become the most important part of

10、 the logistics. As the core distribution vehicle delivery of goods set of goods, distribution and delivery process is paid more and more attention, how to select the optimal delivery route, is the quality of the whole logistics test, the relationship between transportation speed and overall logistic

11、s service cost and economic benefit. With the rise of e-commerce, the new logistics model to set the goods work and distribution operations as the main body has been formed.2 classification and optimization algorithm of vehicle optimal scheduling problem2.1 classification of vehicle optimal scheduli

12、ng problemAccording to the different nature, the vehicle optimal scheduling problem can be divided into different types.According to the transportation task, the vehicle scheduling problem can be divided into three kinds, that is, pure packing, pure unloading, and loading and unloading mixed three k

13、inds of problems.According to the load situation of vehicles, the optimal scheduling problem can be divided into two categories, that is, full load and non full load. Full load refers to the amount of goods is larger than the amount of vehicles, the need for multiple car transportation. Non full loa

14、d means that the amount of vehicles is larger than the amount of goods, and a car can accomplish the task.According to the type of vehicle, the vehicle scheduling problem can be divided into two categories, namely, single vehicle model and multi vehicle model.According to whether the vehicle is retu

15、rned, the vehicle scheduling problem can be divided into two categories, namely, vehicle opening (vehicle not returning) and vehicle closure (vehicle return).According to the optimization goal, the vehicle scheduling problem can be divided into two kinds, that is, single objective and multi-objectiv

16、e problems.The vehicle scheduling problem can be divided into two categories according to whether or not there is a rest time.2.2 optimal algorithm for vehicle scheduling problem2.2.1 exact algorithmExact algorithm, also called optimization algorithm, refers to the algorithm for finding the optimal

17、solution. There are many algorithms, such as cutting plane method, network flow algorithm and so on.One drawback of the exact algorithm is that the amount of computation increases greatly with the size of the problem that needs to be solved. Due to this drawback, exact algorithms can only be adapted

18、 to solve smaller problems. Because of the poor adaptability of the exact algorithm, this algorithm is most suitable for solving a specific problem, so this algorithm is not very popular in practical applications.2.2.2 heuristic algorithmThe heuristic algorithm is completely different from the exact

19、 algorithm. It pursues the satisfaction of the problem rather than the optimality. It is a kind of algorithm constructed by intuition and experience. So far, there have been many heuristic algorithms, the most important are the following two algorithms.Structure heuristic algorithm, its essence is t

20、o be in accordance with the standard will not be in the same line of all points, one by one increase. At every step of the algorithm,After comparing the current line configuration with the other line configuration, the final feasible configuration is improved. The representative algorithms of this k

21、ind of algorithms are nearest neighbor method, scanning method, saving method and so on.Intelligent Heuristic algorithm is developed on the basis of heuristic algorithm of artificial intelligence. Its main algorithms are ant colony algorithm, neural network algorithm and so on.The heuristic algorith

22、m is divided into classical heuristic algorithm and modern heuristic algorithm in solving large-scale PDPTW problem.Classical heuristic algorithms include path construction algorithm and path reconstruction algorithm. The essence of the path construction algorithm is the decomposition algorithm, whi

23、ch is to solve a problem in two stages (routing and sorting). The path transformation algorithm is improved in the path construction algorithm, the first stage is to find a feasible solution, the next stage is to adjust the client, to meet the feasible conditions, to adjust the path, make it more op

24、timization than the current path, has been in accordance with this optimization to optimize it, until not far.The most important of modern heuristic algorithms are tabu search algorithm and simulated annealing algorithm.Tabu search algorithm is a kind of deformation of tabu search algorithm, and it

25、is a kind of modern local search technology. The essence is that the algorithms that have been repeatedly searched in the near future are disabled. It has the advantage of reducing the number of movements to consider and eventually reducing the computational time. The improvement stage and the mixin

26、g stage are the main steps of the tabu search algorithm, one is to get the optimal solution, and the other is to jump out the optimal solution.Simulated annealing algorithm. The specific process of the algorithm is to randomly select a good and a poor feasible solution at each iteration of the feasi

27、ble solution, so as to avoid falling into the local optimal solution. The disadvantage of this algorithm is that it is slow to execute. Based on this drawback, several optimization algorithms are proposed, and these algorithms are effective in practical applications.2.3 dynamic solution algorithmCom

28、pared with the former two methods, the problem of dynamic vehicle scheduling problem is relatively large and relatively difficult to solve. And the requirement of this algorithm is that the corresponding real-time information is needed in a short time. The dynamic solution algorithm is divided into

29、re optimization strategy and local optimization strategy from the solution strategy.2.3.1 re optimization strategyThe re optimization strategy is that when a new real-time information is received, the vehicle path of the optimal vehicle from start to finish should be restarted. The essence is the st

30、atic method to solve the dynamic problem. The study of vehicle scheduling problem is a successful example of the use of a new optimization strategy. In addition, the static algorithm of multiplier adjustment is adopted in the dynamic bicycle problem. The algorithm process is: when new real-time info

31、rmation is used, the dynamic re optimization method is adopted, but this algorithm can solve ten problems at most.The drawback of the re optimization strategy is that each time the new real-time information is received, the design should be re optimized so that when the real-time information is rece

32、ived, the amount of computation is larger. When there is a problem that needs to be solved quickly, there is no time to re optimize it, so the algorithm is not practical.2.3.2 local optimization strategyThe essence of the local optimization strategy is to draw up the template of some paths in advanc

33、e. When the real time information is received, a search is made in the template that is prepared in advance, and a suitable path is used. Compared with the re optimization strategy, the path may be poor, but the amount of computation is greatly reduced, thus saving much time. Local optimization stra

34、tegy is more suitable for the actual vehicle scheduling, so it has attracted more and more attention. The insertion method is more suitable and then put forward the improved method of insertion, the specific method is: when receiving new real-time information, not directly optimize scheduling, but w

35、ait for the future demand, which can reduce its short-sighted behavior. The insertion method and the optimization algorithm can be used together, and better solutions can be obtained after the optimization of the path.3. Research status of vehicle optimal scheduling problemThe optimization of vehicl

36、e scheduling problem in foreign countries is faster than the domestic development. Its development has been involved in various fields, whether large-scale vehicle scheduling such industrial materials transportation, freight transportation, online shopping and distribution chain of goods sending, or

37、 newspapers, and other minor aspects of milk delivery such as use of route optimization will get ideal economic benefits. The most typical example is the world famous Wal Mart Company, which is the use of the most advanced logistics command system so it will be way ahead in the peer. With the in-dep

38、th study of the optimal scheduling problem of logistics and distribution vehicles, the optimal scheduling of logistics distribution vehicles not only develops in the automotive field,It is also used in aviation, ships and so on. In the near future, I believe that the field of development will be bro

39、ader.In our country, the development of vehicle scheduling problem is nearly thirty years later than that of foreign countries, so the research of vehicle routing problem in our country is still relatively backward. Because of Chinas research in this area started late, for the study of the general t

40、heory is not deep enough, coupled with our proposed though but are improved on the specific algorithm for the application of the problem, and there is no innovation, so our country in the vehicle scheduling problem cannot meet the requirements of the development of distribution industry and logistic

41、s industry the. With the increasingly important position of the logistics industry in the market. In order to overcome the limitations of vehicle optimization in our country, the vehicle scheduling problem has been studied deeply in our country, and the initial success has been achieved.4 ConclusionWith the development of logistics and distribu

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