The logistics management a transportation system "point of departure – point of destination" in real time regime
Analysis of the transport system management "point of departure - destination" in real time. The effectiveness of the application in this process of a line of methods based on the use of methods of the theory of fuzzy sets and artificial neural networks.
| Рубрика | Транспорт |
| Вид | статья |
| Язык | английский |
| Дата добавления | 29.04.2019 |
| Размер файла | 13,5 K |
Отправить свою хорошую работу в базу знаний просто. Используйте форму, расположенную ниже
Студенты, аспиранты, молодые ученые, использующие базу знаний в своей учебе и работе, будут вам очень благодарны.
Размещено на http://www.allbest.ru/
1
Размещено на http://www.allbest.ru/
The logistics management a transportation system «point of departure - point of destination» in real time regime
The purpose of the article is to increase the efficiency of logistic management of the transport system «point of departure - point of destination» («PDep - PDes»). The purpose achievement is possible using the methods of the theory of fuzzy sets and neural networks, allowing to consider various ambiguities and indeterminacy in the processes of material flow's management in real-time.
In recent years much attention is paid to a problem of planning, organization and management of work of the logistic delivery systems of goods in the conditions of risk and uncertainty of environment. However, existing methods of control consider influence of uncertain factors only when studying separate links and elements of channels of products distribution. Besides, probabilistic-statistical model are used mainly at disclosure of influence of uncertainty in problems of logistic management [2].
Effective delivery of goods in conditions of the dynamics and environmental indeterminacy associates with a high level of logistic management. This raises the problem of creation of the new organization of cargo delivery process that ensures the operation's stability of separate links in the logistics delivery chain depending on the requirements to the process of delivery [1].
The efficiency of the logistics cargo management is achieved through coordinated interaction of separate parts and elements of the logistics chain of cargo delivery in the system «place of departure - place of destination» by rapid response to the incoming current information about changing the conditions at all stages of the transport process.
It's necessary to process a large flow of complex information about the current state of the transport system's objects, managing cargo in real time. So the use of artificial neural networks is proposed [4].
The process of cargo delivery in the system «PDep - PDes» is presented by the following stages: shipment at the shipper enterprise; the transportation of goods to the destination with selecting the type of transport and route; unloading at the destination point.
Each stage is characterized by a set of parameters that reflect the level of transport service, which at the design stage are fuzzy linguistic variables, so it is reasonable to use fuzzy sets [3].
It's required to choose the most efficient route of cargo delivery with the required level of the transport service adequacy. For solving the problem the method based on fuzzy neural network ANFIS in MATLAB has been proposed. The General sequence of the process of developing hybrid network models can be represented by the following steps:
1. Preparing the file with the training data.
2. You should open the ANFIS editor (comand «anfisedit») and upload a file with the training data.
3. After preparation and uploading the training data you can generate the structure of the FIS system (Sugeno type).
4. After generation the hybrid network, you can visualize its structure.
5. Before the hybrid network training, you should set the training parameters (the method of hybrid network training, the level of training error, the number of cycles).
6. Further configuration options of built and trained hybrid network can be done using standard graphical tools of the package Fuzzy Logic Toolbox.
7. The next step is testing of fuzzy system and the output of results in the visualization.
8. Now we should verify the adequacy of the constructed fuzzy model of hybrid network. To solve this task, you should use the function «evalfis». The results of the forecast for the specific input is obtained by typing the following code in the command area:
x = [1 70 7 3 70 3000]% «The input parameters»; fis = readfis ('set1.fis')% «Upload file»; y = evalfis (x, fis)% «Conclusion of the forecast».
The obtained value of the output of the linguistic variable «adequacy of transport service» for membership function y=0,7 is the result of solving the problem of fuzzy inference for the proposed linguistic values of input variables at a certain stage of rational delivery route selection. It means the less time of cargo delivery to the destination.
The obtained results give grounds to speak about the possibility of practical application of the neuro-fuzzy network to improve the efficiency of logistic management of the cargo delivery transport system.
Further researches consist in developing fuzzy situation networks for operational decision-making in the management of all participants interaction at the delivery system in real time.
Conclusions:
1. The proposed approach of coordinated interaction of the transport system elements and parts «PDep - PDes» allows to reduce the time of cargo delivery.
2. On the basis of this experiment we can make the conclusion that the use of ANFIS for solving the problem of coordination of logistics chains interaction is very promising. The disadvantage is that the quality of the results depends on the quality of experimental data or training data. Therefore, the selection of training data is an important process in using ANFIS.
List of references
transport management departure destination
1. Gubenko V.K. Efficiency of the logistics system of cargo delivery/ V.K. Gubenko, Y.A. Nefedov, A.A. Lamsin // Visnyk Priazovskogo sovereign technical University. - 2007. - №17, p. 23.
2. Nefedov Y.A. Logistic management of the transport system maintenance «metallurgical enterprise - port» in real time: dis. on competition of a scientific degree of cand. the technology. sciences: 05.22.01 / Nefedova Yana Igorevna. X., 2010, p. 167.
3. Leonenko A.V. Fuzzy modeling with MATLAB and fuzzyTECH / A.V. Leonenko - SPb.: BHV-Petersburg, 2003, p. 45.
4. Stovba S.D. Designing fuzzy systems by means of MATLAB / S.D. Stovba - M.: 2007, p. 89.
Размещено на Allbest.ru
...Подобные документы
Понятие и классификация международных авиаперевозок, современные тенденции развития и оценка дальнейших перспектив. Сравнительное описание систем "point-to-point" и "hub`n`spoke". Анализ проблем гражданской авиации Казахстана и пути их разрешения.
курсовая работа [673,8 K], добавлен 11.02.2016International airports serving Moscow. A special program of creating night bus and trolleybus routes. The formation of extensive tram system to transport people. The development of the subway to transport passengers to different sides of the capital.
презентация [4,7 M], добавлен 08.08.2015Description and operating principles of Air-Conditioning System of Tu-154. Principal scheme of ACS. Theoretical base of algorithm developing process. Functions of the system failures. Description of obtained algorithm of malfunctions discovering.
курсовая работа [27,7 K], добавлен 01.06.2009Diesel fuel is any fuel used in diesel engines. Chemical composition and cetane number. Boiling point and freezing point of representative diesel fuel hydrocarbons. Disadvantages of Diesel Fuel. Environment hazards of sulfur. Fuel value and price.
реферат [39,2 K], добавлен 25.05.2012The methodology multiple models and switching for real–time estimation of center of gravity (CG) position and rollover prevention in automotive vehicles. Algorithm to determine the vehicle parameters. The efficacy estimation switched controller scheme.
статья [238,6 K], добавлен 28.05.2012The first rapid-transit system. History Metropolitan Railway. Network topologies, construction stages of London's Metropolitan Railway. Safety and security. Infrastructure 5-Line of Metro de Santiago (Chile), The Soviet Union's stations, Stockholm metro.
презентация [1,2 M], добавлен 13.05.2014Характеристика стандартных единиц отгрузки. Основные параметры международных перевозок железнодорожным транспортом. География деятельности холдинга STS Logistics, оказываемые услуги. Особенности доставки грузов STS Logistics в/из Китай и Европу.
дипломная работа [958,0 K], добавлен 06.11.2011Применение системы нейтрального газа (onboard inert gas generation system) на воздушное судно Boeing 767. Система питания двигателей. Доработка топливной системы путем установки системы нейтрального газа. Встроенные средства диагностики контроллера.
дипломная работа [5,5 M], добавлен 22.04.2015Business strategy of NAC "Uzbekistan airways technics". Modernization and unification of the fleet, expansion of production capacity for technical servicing of aircraft. Process design aircraft repair of composite panels. Total price of modification.
дипломная работа [1,1 M], добавлен 23.05.2015Construction of zone and flight plan. Modeling of zone in experimental program "Potok". Analysis of main flow direction of modeled airspace. Analysis of modeled airspace "Ivlieva_South" and determination of main flow direction, intensity, density.
курсовая работа [2,0 M], добавлен 21.11.2014The car as an integral part of people's lives. Design as a factor of business success in the automotive industry and transport engineering. The transition to an integrated supporting structures instead used on American cars spar frame side members.
презентация [6,3 M], добавлен 23.04.2015Дослідження світовіх інтеграційніх процесів. Аналіз діяльності лідера морських перевезень "Maersk line" та факторів що впливають на її результати. Конкурентоспроможність підприємства. Інвестиції як основа стійкого функціонування судноплавних компаній.
дипломная работа [2,0 M], добавлен 19.06.2016Logistics as a part of the supply chain process and storage of goods, services. Logistics software from enterprise resource planning. Physical distribution of transportation management systems. Real-time system with leading-edge proprietary technology.
контрольная работа [15,1 K], добавлен 18.07.2009Evaluation of urban public transport system in Indonesia, the possibility of its effective development. Analysis of influence factors by using the Ishikawa Cause and Effect diagram and also the use of Pareto analysis. Using business process reengineering.
контрольная работа [398,2 K], добавлен 21.04.2014Essence, structure and basic functions of informational logistics system. Principles and the levels of information logistic system. Resources project development. Business process of logistic operations. The tariff for the transportation of cargo.
дипломная работа [3,1 M], добавлен 31.05.2013Initial data for the term paper performance. Order of carrying out calculations. Analyze uncompensated system. Synthesize the real PD-compensator ( ) which would guarantee desired phase margin at gain crossover frequency . Analyze compensated system.
курсовая работа [658,7 K], добавлен 20.08.2012Teaching to the teaching methods. Diagnostics of organization. Managers are from a personnel. Basic processes which must exist in a company, from the point of view of management human capitals. Objects of estimation. Conduct (values, relations, opinions).
реферат [28,9 K], добавлен 27.10.2010Methodological characteristics of the adaptation process nowadays. Analysis of the industrial-economic activity, the system of management and the condition of adaptation process. Elaboration of the improving project of adaptation in the Publishing House.
курсовая работа [36,1 K], добавлен 02.04.2008IS management standards development. The national peculiarities of the IS management standards. The most integrated existent IS management solution. General description of the ISS model. Application of semi-Markov processes in ISS state description.
дипломная работа [2,2 M], добавлен 28.10.2011A cosmological model to explain the origins of matter, energy, space, time the Big Bang theory asserts that the universe began at a certain point in the distant past. Pre-twentieth century ideas of Universe’s origins. Confirmation of the Big Bang theory.
реферат [37,2 K], добавлен 25.06.2010
