Name
Arinichev Igor Vladimirovich
Scholastic degree
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Academic rank
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Honorary rank
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Organization, job position
Kuban State Agrarian University
Web site url
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Articles count: 4
The mathematical model of the basic production assets which one can be used by a small enterprises at the justification of planned solutions of productive activity is tendered and verified
The article proposes the method of determining the norm of reinvestment of net income in the fixed assets of a small business, which yields the highest value of the sum of its savings fund
The article presents the methods of specialists’ distribution
for a consulting company between its projects in
accordance with the methodology of dynamic programming
for expected profit maximization.
For its implementation, a mathematical model is being
formed with nonlinear objective function and linear
restrictions. The non-linearity of the objective function
is due to the specifics of consulting companies and
their size. The model includes probability parameters
determined by expert evaluations method based on previous
experience of the company in the analogical
works and describing successful implementation of
each project in its portfolio. Then the parameter and
function of the state, satisfying recurrence are considered
and linear replacement is performed to reserve a
minimum number of experts on each job. The article
gives a hypothetical example of a consulting company,
including in its portfolio five projects with the mentioned
profits in case of their success. On its basis, the
developed method is implemented as a 5-step procedure
of modeling of unknown parameters. Economic
impact of the methods’ application is estimated . The
developed model and method can be used by specialists
in consulting companies, as well as in service industries
The article presents an algorithm for constructing an
expert system for quantitative bankruptcy risk
estimation of small agricultural enterprises. Fuzzy logic
analysis methodology in the form of fuzzy inference
system was put as a basis for this development,
classically including five steps: fuzzy rules base
forming, fuzzification, aggregation, intensification,
defuzzification. All the calculations were performed
using MATLAB 2012 software package including
Fuzzy module. Demand and costs of production were
proposed as main factors influencing bankruptcy risk.
Quantitative estimations of input parameters were
determined by 100-point scale on the basis of expert
estimations, and after that variables were fuzzificated in
the form of trapezoid numbers as most common in
fuzzy logic analysis (after triangular). Besides
quantitative estimation of bankruptcy risk a surface of
fuzzy inference was constructed, allowing to determine
dependence between output variable’s values and input
variables’ values of original bankruptcy risk model, as
well as necessary values of input variables values to
reach acceptable level by experts