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Моделирование цепей поставок услуг сельского хозяйства на базе сети Петри

УДК 33.055

Моделирование цепей поставок услуг сельского хозяйства на базе сети Петри

Чжао Хоуфу

аспирант Красноярского ГАУ

г. Харбин, Китай

E-mail: zhaohf@yandex.ru

В данной статье дается анализ и современное состояние современных сельскохозяйственных цепей поставок в Российской Федерации, что способствует их оптимизации, а также приводится ряд причин, почему эта сфера  имеет особую  важность.

Ключевые слова: цепь Петри, модель цепи поставок, экономика, сельское хозяйство, количественный анализ.

 

Modeling the service chain of modern agriculture based on the Petri net

Zhao Houfu

post-graduate student of Krasnoyarsk SAU

Kharbin, People's Republic of China

This article provides an analysis and the current state of modern agricultural supply chains of the Russian Federation, which contributes to the optimization of the supply chain, and also gives a number of reasons why this area is of particular relevance.

Key words: Petri chains, supply chain model, economics, agriculture, quantitative research.

 

Agriculture has a complex supply chain structure, from production, packaging, warehousing and transportation of agricultural products to the final sales process, logistic and capital. In this regard, there are particular problems which can be associated with the need to deal with new issues.

In the existing agricultural supply model, the supply chains are based on individual farmers who are decentralized, while the number of centralized agricultural production bases is much smaller. These farmers use their own feelings and knowledges of the agricultural market. Therefore, they produce decentralized products, and after basic packaging, they transport them by themselves to local markets or farmers' markets for further sale. Due to restrictions on storage conditions and the complexity of logistics, most products are difficult to sell to remote areas, which impedes the promotion and distribution of products, which is extremely unfavorable for long-term development.

Taking into account all this issues, it’s quite necessary nowadays to conduct a quantitative study and comparative analysis of the existing model for the supply of agricultural products by modeling Petri nets around the relationship between information flow, logistics and capital flows, in order to use modern information management technologies. The current agricultural supply model is adjusted in such a way to ultimately improve the operational efficiency of the entire supply chain and achieve the greatest benefits.

First of all, a qualitative analysis of the composition is required before establishing operational models of the current agricultural supply system. It is known that at present, the supply of agricultural products mainly includes the following links, as shown on a diagram 3-1:

alt

Diagram 1. The traditional mode of supply of agricultural products

 

It is necessary to perceive this relevant information in a timely and effective manner and play an appropriate role in certain links, thereby guiding the work of the entire supply chain. From the obtaining of market demand to the final process of consumption of agricultural products, which contains a huge amount of information, such as: market demand, product price, quantity of products, processing time, stocks, transportation conditions and market sales, as well as manufacturers, processing companies, logistics, sellers and consumers etc.

However, due to the lack of effective support for the information platform in the existing supply model, the flow of information between links is blocked. It makes difficulties for communication between manufacturers, processors, logistics and sellers. These problems lead to a traditional supply model, and in order for independent business farmers to control effective information, they must do all the work of manufacturing, processing, transporting and selling directly to the consumer for sale, as shown on a diagram 2:

587

 

Diagram 1. Decentralized individual farmers’ business model

 

These decentralized farmers do not need to work with other operators to independently track the movement of products from their production to the final point of consumption in order to get the most benefit. Because of the simple management and direct advantages of this supply model, individual farmers in almost all regions of China apply this model of independent work, which has formed the current status of the current agricultural supply chain in Russia.

Despite the fact that this supply model has a long history and can mainly maintain the current balance of supplies of Russian agricultural products, today, in the era of informatization, it is gradually revealing a large number of problems. Therefore, a big variety of questions are arised. For instance: Is it possible to get the maximum benefit in this mode of operation? In what kind of links consist the problems? What are the risks of it? Is the adaptation of agricultural supply chains to long-term development possible? Etc. This series of problems, in the absence of appropriate quantitative studies, will be difficult to identify only with the help of empirical judgment and explain all the advantages with more than one comparison.

In the context of current highly competitive environment in the agricultural market and the frequent occurrence of problems, it is vital to conduct a comprehensive quantitative analysis of the current supply model in order to improve the current model of the agricultural supply chain, as well as improve operational efficiency and shorten the work cycle.

In contrast to the excellent research schemes for this issue, the model obtained by modeling the Petri net can describe all the types of possible variations and solutions. Various links in the current work of the supply chain of agricultural products in graphical and quantitative form and combines a qualitative analysis with a quantitative description. This will initiate a quantitative comparative study of the supply chain work cycle and operational efficiency.

Literature

1. Jennifer Blackhurst, Tong (Teresa) Wu, Christopher W. Raghead. Asystematic approach to detecting supply chain conflicts with hierarchical expansion of the Petri net // Omega: issue 36, No. 5, 2008. P. 680-696.

2. Report on the status and use of agricultural land of the Russian Federation in 2014. Ministry of Agriculture of the Russian Federation, 2016.

3. Klimova N.V., Ishchenko M.I. Export Potential of Agriculture in Russia // Political Mathematical Electronic Scientific Journal of the Kuban State Agrarian University: vol. 119, 2016.

4. Liu Zhaoyun, Sun Shimin, Wang Jiyong. Research Progress and Agricultural Supply Chain Management Trends in China // Business Research: vol. 3, 2009.S. 161-165.

5. Ma Xiaoing, Jiang Changjun. Modeling and analysis of supply chain management based on Petri time No // Computer Engineering: no. 29, No. 1, 2003. S. 82-84.

6. Ministry of Agriculture of the Russian Federation (2014). State program for the development of agriculture and regulation of agricultural products, raw materials and food markets for 2013-2020. (as amended on December 19, 2014).

7. Sun Liang, Wang Xiaoyuan, Yu. Shaovei, Meng Hua, Zhou Tao. Modeling and simulation analysis of the supply chain of agricultural products in the face of market uncertainty // Journal of Agricultural Mechanization Research: vol. 9, 2011.

8. Tsui Zhengdong, Liu Jin. Supply chain modeling and analysis based on generalized stochastic Petri nets // System Engineering - Theory and Practice: vol. 25, No. 12, 2005.S. 18-24.

9. Yuan Chong. The principle of the Petri net [M.]. Beijing: Electronic Industry Publishing House, 1998.

10. Yang Chungang, Jiang Changjun et al. Modeling and analysis of the workflow of integrating medical information based on the Petri net // Journal of System Engineering, vol. 18, No. 6, 2006. S. 1696-1704.

Материал размещен кафедрой «Логистика и маркетинг в АПК» Красноярского государственного аграрного университета
Источник: Материалы XV Международной научно-практической конференции «Логистика – Евразийский мост» ЛЕМ - 2020


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