=Paper=
{{Paper
|id=Vol-3040/paper9
|storemode=property
|title=Mathematical Formation Model of the Logistic Digital Platform in the Agro-Industrial Complex
|pdfUrl=https://ceur-ws.org/Vol-3040/paper9.pdf
|volume=Vol-3040
|authors=Viktor I. Medennikov
}}
==Mathematical Formation Model of the Logistic Digital Platform in the Agro-Industrial Complex==
https://ceur-ws.org/Vol-3040/paper9.pdf
Mathematical Formation Model of the Logistic
Digital Platform in the Agro-Industrial Complex *
Viktor I. Medennikov (0000-0002-4485-7132)1(*)
1 Federal Research Center “Informatics and Control” of the Russian Academy of Sciences,
Moscow, Russia
dommed@mail.ru
Abstract. The paper focuses on analyzing the state and trends of digital
agricultural transformation in the developed countries and the Russian
experience of AIC informatization. The work considers the possibility of
forming a digital logistics platform as a connection of all participants in the
value chain. The chain includes product manufacturers, resource suppliers,
product consumers, and logistics companies, excluding unnecessary
intermediaries. The digital technologies evolution from the digitalization of
individual operations to the digitalization of an interconnected complex of
operations serves as the basis for developing a digital logistics platform.
This is relevant not only in agriculture but also in related industries,
integrating all operations based on cloud technologies. We consider the
scientific foundations for designing a digital logistics platform for AIC
based on mathematical and ontological modeling, integrated into a single
digital platform for managing the country’s economy. We provide an
analysis of the state of the Russian logistics industry, which hinders the
development of the economy. It is important to emphasize that the concept
of the national platform “Digital Agriculture” prepared by the Ministry of
Agriculture at the end of 2019 does not pay attention to integrating
information resources and systems and developing logistics activities.
Keywords: Logistics · Digital platform · Mathematical modeling · Agro-
industrial complex
1 Introduction
We analyzed the experience of digital agricultural transformation in various
countries. We found that depending on the possession of financial, labor, material,
and technical resources, social capital focuses on the most effective, from their
point of view, directions of this global process. Based on these data, the following
basic principles of digital transformation are highlighted:
• Creation of an information management system that collects, processes, stores,
and distributes the necessary data. For this, there is a form adapted to the daily
*Copyright © 2021 for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
farm operation, based on the widespread integration of disparate data into a
single system;
• Precision agriculture, i.e., time and place-verified production process control.
This, in turn, improves its economic characteristics, reduces the burden on the
environment;
• Use of satellite navigation systems, images of fields obtained using remote
sensing of the Earth, allowing one to create a card index of data on soil
characteristics, crop yields, moisture, nitrogen content, etc.;
• Active introduction of automation and robotization at all levels of agricultural
work;
• Revision of the ideology, technology, and organization of enterprise
management, formalized in the form of standards, as a result of the fusion of
information technologies and technologies of people management;
• Personnel training with new competencies.
In the context of the first principle, J’son & Partners Consulting (IKS-MEDIA,
2018) believes that agriculture has two distinct platforms: aggregator platforms for
industry information or platforms for primary collection and accumulation of data
(“information resources”) and applied platforms (“applications”). It is regarded
that the interaction between them must be based on cloud technologies and
services since only this model makes them available to farms of all sizes, and not
just for some of the largest.
The emergence of digital cloud services available to all farms creates the
necessary prerequisites for dramatically increasing efficiency and reducing
industry risks. It is actual for all value chain participants, including resource
suppliers, product consumers, and logistics organizations. The introduction of
such a cloud-based approach in the agricultural sector is just beginning to be seen.
The highlight of the digitalization of AIC is that the widespread introduction of
digital technologies, including agricultural production, makes it possible to switch
to a new type of production enterprise. Production begins to be based on the
principle of current control of all operations, which will make it possible to perfect
the production process (Medennikov & Raikov, 2020). This will make it possible
to implement the predictive principle of building agricultural production, based on
a deep analysis of the entire set of data on fluctuations in supply and demand,
opportunities, availability of resources, financing, and other equally important
components of the entire chain from production to consumption, moreover,
requiring information compatibility of the flow data along the entire chain.
Logistics was among the first industries to realize the need for an integrated,
systematic approach to managing its activities based on innovative IT solutions.
The ability to continuously monitor material flows in real-time in remote access
modes through information systems played a decisive role in this approach. With
this system, potential opportunities for production, supply, and consumption are
covered with the transition to integrated electronic logistics (Toluev &
Plankovsky, 2009; Ereshko, Medennikov, Baida & Gaidash, 2018). However, the
insufficient level of integration of information systems of organizations
participating in specific supply chains, disordered, chaotic development of new
opportunities of Internet technologies leads to the emergence of many
intermediaries in the entire value chain. Therefore, the spontaneous process of
integrating the platform-aggregator of information resources and the application
platform for all participants in the value-added chain needs a theoretical
justification, which is proposed in this work.
2 Materials and Methods
In Russia, the conceptual issues of this approach have been studied. This study
occurred as a result of calculations based on the model for the synthesis of optimal
information systems (IS) (Medennikov, 1993) as the “Agricultural
Electronization” task of the Comprehensive Program of Scientific and
Technological Progress (STP) of the Member States of the Council for Mutual
Economic Assistance (CMEA). Later, this approach was theoretically
substantiated in several works (Zatsarinny & Shabanov, 2017; Flerov &
Vyshinsky, 2018; Medennikov, 2018). Thus, an economic and mathematical
model for the formation of digital platforms [DP] for managing the country's
economy was developed, which allows calculating the optimal DPs in AIC
(Medennikov, 2019). The model singled out several digital sub-platforms, a cloud
service for collecting and storing operational primary accounting information of
all enterprises in a single database [SDPA]. The second is also a cloud service of a
unified technological accounting database [SDTA] of all enterprises with an
ontological information model, for example, crop production formed based on
SDTA and SDPA, common for all agricultural enterprises in Russia (standard for
information resources [IR]) with the allocation of 240 functional management
tasks with a unified description of algorithms also for most agricultural
organizations (application standard). Similar work was done for all branches of
agricultural production and 19 types of processing enterprises.
The requirements for information compatibility of data along the entire value
chain are a powerful incentive for logistics to implement current integrated
information technologies. The prospects for the development of logistics activities
are becoming more transparent with distributed ledger technologies. This is also
facilitated by forming a single information Internet space for the country’s digital
interaction.
Since logistics was one of the first industries that realized and felt the need to
integrate disparate logistics processes into a single system, then leadership
developments in this direction should have appeared here. Logistics was the first
to carry out ontological activity modeling to establish specific standards for terms
and concepts accepted globally. In particular, in the form of the SCOR-model
(Supply-Chain Operations Reference model), developed by the International
Organization-Supply Chain Council (The Supply-Chain-Council-SCC) (“SCOR-
model,” 2017).
As a result of the improvement of ICT and the acquired experience in logistics,
the following levels of integration of their activities occurred (Ereshko et al.,
2018).
• Subcontracting Supply Network [SSN] is an association of legally independent
organizations, interconnected only by contracts, collaborating, and
implementing the general movement process of products from raw materials to
the final consumer.
• Information Subcontracting Network [ISN] is also an association of legally
independent organizations forming a single information space of technological
resources. The final product or service is produced based on the operational
allocation of resources. Through the developed website, within the ISN, one
can find a supplier, an order, and place one’s information.
• Production and Logistics Network [PLN] combines the concepts of SSC and
ISN and is the highest point of logistics activities integration. Unlike ISN,
which is a kind of “bulletin board,” in the PLN, a single information space
[SIS] is a platform for planning and managing projects on the Internet, with a
shared database in the “cloud” data on the performance of logistics operations,
classifiers, and standards common to all registered participants.
In the concept of PLN, the SIS includes only a small part of autonomous
enterprises with a limited set of information content. This is for the integrated
planning purpose and management of implementing a limited set of projects in the
network (Medennikov, 2018). In turn, based on the proposed economic and
mathematical model for digital platforms forming, the concept of forming a single
information Internet space of digital interaction [SIIS DI] of all enterprises and
organizations of industries, country, including AIC. We believe that it is necessary
to create a unified system for collecting, storing, and analyzing primary
accounting and statistical information. This information is integrated with a
unified system of classifiers, reference books, standards representing the registers
of practically all material, intellectual and human resources based on ontological
modeling of these types of information resources. This digital platform can form
supply chains of arbitrary configuration with the participation of the majority of
economic entities in almost all country’s sectors.
3 Results
We formalize the most popular external logistics management system. The goal is
more efficient analysis, planning, and design of supply chains. In this case,
participants in the supply chain are the following groups: suppliers, consumers,
warehouses, and transport companies.
The goal is to form optimal logistics chains to supply products to consumers
by transport companies using warehouses based on minimizing the total costs of
products, their transportation, and storage services. At the same time, there should
be a choice of suppliers of products, a choice of warehouses, and transport
companies with loading vehicles. The tasks are solved in a complex way: tracking
transport, managing orders (requests), managing transport costs, and warehouse
services. We believe that there are enough transport companies to satisfy all needs,
and the supply of goods exceeds demand. It is assumed that there is a systematic
control process with a T period and that all logistic operations are averaged over
time.
We do not consider such characteristics of vehicles as capacity, transported
cargo volume, etc. We consider the actual capacity of the vehicle with the specific
capacity. For the unit of the product, the supply volume of storage, we take both
the unit and the volume of the specific capacity of the product.
Mathematical model
The notation is the following:
vik – demand volume of i – comsumer in k – product, i ∈ I , k ∈ K .
w jk – availability volume of k – product of j – supplier j ∈ J .
p jk – unit price of k – product of j – supplier.
n – transport company size (TC), n ∈ N .
s – warehouse number, s ∈ S .
r – number of vehicle category (V), r ∈ R .
Rn – amount of categories V of n-TC.
N rn – V amount of r–category of n-TC.
g rn –V number of r–category of n-TC.
µ r – specific capacity of the vehicle r–category of V, calculated as the ratio of the
total product weight to their volume intended for transportation r–category of V
As – warehouse capacity s (according specific capacity), calculated in accordance
with converting pallet capacity table into specific capacity
Gr – passport capacity of r – category of V
Vr – body space r– category of V
d r = min ( µ r , G / V ) – actual capacity of r – category of V with the specific
r r
capacity
Drn – sum of actual capacity of all V’s of r – category of n – TC with specific
capacity, Drn = d r * Rn .
d ks – unit storage and handling rates of k – product in s – warehouse, this value
reflects the amount of average specified costs for the T. period
f irnsh
1
– transportation prices of a product unit from s – point to I – point (delivery
place of i – consumer) r – category of V of n – TC through h – point, according
the specific capacity r – category of V, h ∈ I .
f jrns2 – transportation prices of a product unit from j – point (product location of j –
supplier) to s – point with r – category of V of n – TC, according the specific
capacity r– category of V
f ijrn3 – transportation prices of a product unit from (without shiftment) j – point to
i – point r – category of V of n – TC, according the specific capacity r – category
of V
Variables:
xijk – delivery volume of k – product from j – point to i – point.
yirns
1
– delivery volume from s – point to i – point of r – category of V of n – TC.
yirnsh – delivery volume from s – point to i-point of r-category of V of n –
1
TC.through h – point.
y 2jrns – delivery volume of k – product from j – point to s – point of r – category
of V of n – TC
yijrn
3
– volume of direct deliveries from j – point to i – point.
yks4 – storage volume of k-product in s-warehouse.
с1 – supplying cost of all products from all s – points to all I – points.
с2 – supplying cost of all products from all j – points to all s – points.
с3 – supplying cost of all products from all j – points to all i – points
с4 – storage cost all products in all warehouses
с5 – total cost of all supplying products.
с0 – total cost of the supply chain
Formulas and inequalities:
∑ xijk = vik (1)
j
∑ xijk ≤ w jk (2)
i
∑ yirns + ∑ y
1 2
jrns
+ ∑ yijrn
3 ≤ Drn (3)
is js ij
∑ yirns = ∑ y (4)
1 2
jrns
irns jrns
∑ xijk = ∑ yirns + ∑ yijrn 1 3
(5)
jk rns jrn
∑ xijk = ∑ y jrns + ∑ yijrn (6)
2 3
ik rns irn
∑ y jrns = ∑k yks (7)
2 4
jrn
yirns
1
= ∑y
1
irnsh
(8)
h
∑ yirns = ∑ yks (9)
1 4
irn k
dr - ε r ≤ y 3
ijrn
– almost full load demand ( ε r – obtainable undercapacity) of
direct product deliveries from j – point to i – point with r – category of V of n –
TC;
dr – ε r ≤ ∑ y 1
irnsh
– almost full load demand ( ε r – obtainable undercapacity) of
i
r – category of V of n – TC when the product supplying from s – point to i – point
through h – point;
∑ yks ≤ As ;
4
k
Effectiveness criterion
с1 = ∑ f irnsh
1
yirnsh
1
(10)
irnsh
с2 = ∑ f jrns
2
y 2jrns (11)
jrns
с3 = ∑ f ijrn3 yijrn
3
(12)
ijrn
с4 = ∑ d y ks
4
ks
ks
(13)
с5 = ∑ p jk xijk (14)
ijk
с0 = с1 + с2 + с3 + с4 + с5 → min (15)
As a result of solving this problem, we obtain specific values: xijk , yirns , yirnsh
* *1 *1
y *jrns , yijrn , yks .
2 *3 *4
4 Discussion
We believe that the digital logistic platform [DLP], based on this structure of the
SIIS DI (the digital platform of the country), can form logistic chains of arbitrary
configuration with most of the country’s participation economic entities.
Also, we consider that the DLP implementation can effectively implement the
distributed ledger technologies and smart contracts in logistics. While the joint
implementation with the SIIS DI will potentially provide real-time tracking of
goods, reduce the workflow, and increase transparency. According to the WTO,
removing barriers in the international supply chain of goods will increase global
GDP by 5% (Ereshko et al., 2018).
The state of logistics, like digitalization, is far from the ideal in Russia. The
world ranking of logistics efficiency in Russia is 95th globally (out of 155
countries on the list). In our country, the level of logistics costs in the economy is
one of the world’s highest. The total internal and external costs are about 20% of
GDP, in China – about 15%, in the EU – 7–8%. As a result, production
inventories exceed this figure in the EU and the USA by 18%. In Japan, the
reserves are 64% lower than the Russian ones (Ereshko et al., 2018).
Thus, inefficient logistics is one of the significant factors affecting the low
rates of development of the Russian economy. If all logistics costs are reduced to
the world average (about 11% of GDP), the country will additionally receive
about $ 180 billion per year (Ereshko et al., 2018).
All participants in the activity understand the need for the digital
transformation of the transport and logistics services market. One of the
significant factors in improving the quality of logistics services is improving the
development of various types of associations between all participants in logistics
chains through the formation of a single information digital interaction. However,
most market participants are waiting for a decision from the government to form
the logistics center and the SIIS DI, since the era of task-oriented design of
information systems under the guise of digital transformation continues in most
industries due to the momentary benefits of this approach.
For example, at the end of 2019, the Ministry of Agriculture developed the
concept of the national platform “Digital Agriculture” (TAdviser, n.d.), which
provides a list of sub-platforms (the composition of which determines the
platform):
• Collection of statistical data of AIC;
• Providing information support and providing services;
• Digital land use and land management;
• Storage and distribution of information materials;
• Traceability of agricultural products;
• Agrometeorological forecasting;
• Service of multifactor operational monitoring, diagnostics, and proactive
modeling of the development of diseases in agricultural crops.
However, this approach to the digital platform of agriculture as the sum of
these sub-platforms excludes their integration on a single AIC DP. There is no
mention of logistics in the concept. This approach to reliance on the market led to
the closure of the Institute of AIC Cybernetics. There is currently no single
research institute in the industry that is comprehensively engaged in research in
the digital economy field. The Timiryazev Academy has also not turned into a
center of competence in this area, nor into a testing ground where the most
advanced, promising digital technologies would be developed.
The formation of a single information Internet space for digital interaction of
all enterprises and organizations of the country (with the creation of a unified
system for collecting, storing, and analyzing primary accounting, statistical,
technical information) will require combining the intellectual and technological
resources of many industries, like space or nuclear programs. These actions should
be directed towards implementing the National Automated System’s project for
the Collection and Processing of Information for Accounting, Planning, and
Management of the National Economics. A. I. Kitov and Academician V. M.
Glushkov proposed this program (Peters, 2016).
5 Conclusion
We believe that the proposed digital logistics platform can become a significant
advantage in the competitive struggle of agricultural enterprises. The main task of
this platform is to reduce the cost of logistics, to solve the problem of trust
between market participants. New markets will open for carriers. Idle runs will be
reduced due to the SIIS DI platform’s availability to a larger number of customers.
It should be noted that the agricultural industry in Russia is not ready for the
transition to SIIIS DI technologies. Including precision farming technologies
based on remote planet sensing, combined by the PLN with digital platforms of
other industries. The way out is seen in the practice that has been worked out for
centuries: the complex development of the most advanced digital technologies
from several references’ objects for subsequent implementation in all country
farms. The Timiryazev Academy should become one of the leading backbone
reference objects.
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