Introduction
    In the conditions of market relations the center of economic activity moves to the basic link of all
economy – enterprise, because products are created, works are executed, services are done exactly on the enterprise.
    An enterprise is a managing subject of market, possessing legal, production and financial independence, foundation of
which is the professionally organized collective, owning production facilities and articles of labor, allowing to it to produce
products, render services and execute works of certain character and setting in a necessary amount, quality and assortment.
    Aims of functioning of enterprise are:
1) receipt of maximal income;
2) account real financial and other resource possibilities;
3) complete satisfaction of necessities of market of sale;
4) maximal decline of production costs, including and maximally possible loading of equipment.
    An enterprise begins development of the program with the certain sphere of activity and expects on your own a production
volume, based on research and monitoring of market of this commodity, financial possibilities of firm and power of enterprise. A
prognosis serves as basis for creation of the marketing program and production plan. His purpose is to give the most credible
alternative ways of prospected market development at the set level of knowledge and mortgaged pre-conditions. [1]
    Planning is raising of problem, prognostication, determination of aims, development of strategy their implementation,
determination of terms and facilities of gaining end. Functioning of the system is provided due to adjusting which includes an
account and control. In the process of planning decisions are made. Then conditions are created for their implementation, and the
system begins to function.
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At national level
    Research such economists conduct on the topic of planning and forecasting of products issue: M. M. Alekseeva,
V. I. Borisevich, I. A. Bokun [2], A. I. Pikalova [3], M. I. Buhalkov [4], V. I. Kuzin [5], A. K. Znamenskyy [6], O. I. Volkov [7],
V. A. Goremikin, V. V. Gluhov, A. I. Ilin, M. V. Makarenko, O. M. Mahalin, V. M. Popov, S. E. Kamenicer [8],
E. A. Utkin, V. V. Carev, R. A. Phathutdinov and so on [9]. Software products are developed for planning and prognostication of
issue of products on an enterprise the followings firms: LTD. "Marka" [10], company "Intellekt-servis" and other.
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At global level
    Questions of planning and prognostication are widely lighted up in works of modern foreign authors R. Akoff,
I. Ansof, G. Benveniste, L. Fogelya [11], J. Bigel, G. Veye, Ch. Gannt, P. Draker, W. Dering, M. Porter, F. Teylor, A. Fayol, R. Falmer,
G. Ford and others. [9] Also foreign firms develop software products for planning and prognostication of issue of products. Such firms
are "1C", "Consistent Software" [12] etc.
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Description of the developed subsystem
    Essence of prognostication and planning of issue of products consists of ground of aims and methods of
their achievement on the basis of exposure of complex of tasks and works, and also determination of effective methods and methods,
resources of all kinds, necessary for implementation of these tasks and establishment of their co-operation. Planning is one of
major condition of organization of effective work of enterprise. Planning engulfs basic directions to economic activity, such as
sales, purchases, production, management money facilities in co-operation between itself. Planning leans against prognostication of
demand, analysis and estimation of present resources, prospects of development of enterprise.
    Optimization of structure of raw material at planning of issue of products is the substantial source of backlogs of
increase of sum arrived. Logically to suppose that an enterprise is advantageous to increase the stakes of those wares which bring
in a maximal income. But always it should be remembered about the row of limitations, not allowing to give up less cost-effective
products:
1) potential demand on products is dynamic enough and differentiated in time and space. Those wares and trade marks which are
claimed presently now can lose the consumer attractiveness through some intervals of time;
2) capital production assets need permanent exploitation, adjusting and service. Outages of equipment are an always unfavorable
factor for a production.
    The plan of issue of products determines:
a) quantitative indexes of production;
b) volume of output, which depends on the followings factors of products:
    - initial size of available production capacities;
    - amount and type of the equipment, his productivity, possibility of the best use, plan of repair;
    - amounts of working hours in the planned period;
    - assortment of products (orders of clients), which depends on a season (time of year), fashion and necessities of
population;
    - resources of raw material and limits of expense of it on unit of products and his quality.
    For every period, engulfed by a plan, it is necessary to define two variables: production volume in this period;
amount of resources in-use in this period. The plan of issue of products reflects a nomenclature and assortment productions
of goods in accordance with the plan of realization, obligations of enterprise and economic conditions.
    Planning and forecasting of the produced products includes the decision of row of tasks. Foremost, demand is forecast
on products, produced by an enterprise. A nomenclature, assortment and volume of output of products, is further planned in
accordance with a prognosis. A nomenclature of production is a list of wares (finished products, ready-to-cook foods, etc.),
subject to making on an enterprise in the planned period. The assortment of products characterizes correlation of specific scales
of separate types of wares in the general issue of products. A nomenclature, assortment and volume of the products made an
enterprise, is set on the basis of the centralized task on supplying with major kinds to the products and brief-case of orders
of enterprise taking into account his specialization. Agreements are thus taken into account on deliveries, celled by an
enterprise.
    The nomenclature of the produced products can suffice vast, an enterprise is equipped by plenty of equipment of
different type and setting. In this case it is expedient to perfect the structure of issue only of that products specific gravity
of which in the general volume of output is high enough.
    The necessary condition of increase of amount of production of certain wares is universality of equipment for their
production. The plan of issue of products can influence on the size of a number of costs, including: costs of storage of the
prepared products; costs of conduct of brief-case of the set aside orders; costs, related to extracurricular work or outage of
workers; costs, related to the transmission of part of works to the subcontractors.
    The task of optimization of structure of raw material at planning of issue of products must decide on every
industrial enterprise which is interested in maximization of income from a sale to the produced products.
    For the normal functioning of computer informative subsystem of planning and prognostication of issue of products the
followings entrance documents are needed:
- report on realization of commodities from storage of the prepared products for a previous month, quarter, year (planned period);
- information about products on beginning of the planned period;
- invoices on materials;
- bills of charges;
- technological maps;
- calculations on produced goods;
- brief-case of orders;
- information about the production capacity of enterprise.
    For the computer subsystem of planning and prognostication of issue of products output documents will be:
- prognosis of issue of products on a certain period;
- plan of issue of products on the basis of prognosis.
    All got output documents in this subsystem are used in future and can be entrance documents in other, contiguous subsystems.
In particular a plan of issue of products is basis for the calculation of the coordinated plans of production subdivisions, workshops
of basic production and providing services. In the number of other information there are reports, queries, diagrams. There is
statistical information in them which can be used by a statistical department.
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Raising of task of optimization
    For planning and prognostication of issue of products the methods of analysis of the systems, mathematical
design, optimization, expert estimations and new information technologies are used.
    That parameter which determines the degree of perfection of decision of arising up problem comes to light for the
decision of task of optimization. This parameter is usually named an objective function or criterion of quality. In economic tasks
it, as a rule, maximization of income. The aggregate of sizes which determine an objective function is further set. Finally, all
limitations which must be taken into account at the decision of task are formulated. After it a mathematical model, consisting in
establishment of analytical dependence of objective function from all arguments and analytical formulation of concomitant to the
task of limitations, is built. So, let it is set as a result of formalization of the applied task, that objective function
,
(1)
where great number X is generalization of limitations, it is named in a number of feasible solutions. The creature
of problem of optimization consists in a search on a great number X – great number of feasible solutions of such decision
, at which objective function f arrives at the least or most value (2).
(2)
    As criteria of optimization choose the followings: limitations will be the maximal loading of equipment
and minimum use of resources, and by an objective function – arrived maximum (3). On the basis of it get a necessity to us decision,
i.e. plan of issue of products.
,
(3)
where qi is a price of i wares; xi is a volume of output i wares; P are expenses; aij is labor intensiveness of
making i wares on j equipment; Ai is the maximal loading j equipment; bir is an amount of resources r, necessary for making i wares;
Br is a minimum volume r resource.
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Decision of planning task by genetic algorithms
    Genetic algorithms are analytical technologies, created and adjusted by nature for millions of years of
its existence. They allow deciding the tasks of prognostication, classification, search of optimum variants, and quite
irreplaceable in those cases, when in ordinary conditions the decision of task is based on intuition or experience, but not
on its strict (in mathematical sense) description.
    Let some difficult function (objective function), depending on a few the variables, is given, and it is required
to find such values of variables which the value of function is maximal at. Tasks are such named the tasks of optimization
and meet in practice very often.
    One of examples is a task of planning of issue of products. In this task variables are volumes of output of products,
and a function which needs to be maximized, is total profit of enterprise. Also there is value of costs of realization of products,
all expenses on every good, norms of charges and fund of time.
    We will make an effort decide this task, applying known to us natural methods of optimization. We will examine
every variant of issue of products (set of values of variables) as an individual, and profitableness of this variant – as
adjusted of this individual. Then in the process of evolution (if we will manage it to organize) the adjusted of individuals
will increase, and, will appear more and more profitable variants of plans. Stopping an evolution in some moment and
choosing the best individual, we will get the good enough decision of task.
    A genetic algorithm is a simple model of evolution in nature, realized as a computer program. Both the
analogue of mechanism of genetic inheritance and analogue of natural selection is used in it. Biological terminology is thus
saved in the simplified kind.
    To model an evolutional process, we will generate in the beginning casual population, a few individuals with the
casual set of chromosomes (numerical vectors). A genetic algorithm imitates the evolution of this population as cyclic
process of crossing of individuals and digenesis. A life cycle of population is a few casual crossings (by means of crossing-over)
and mutations as a result of which to population some amount of new individuals is added.
    A selection in a genetic algorithm is a process of forming of new population from old, old population
perishes whereupon.
    A selection in a genetic algorithm is closely related to principles of natural selection in nature.
    After a selection to new population the operations of crossing-over and mutation are again used, after
again there is a selection, et cetera.
    Thus, the model of selection determines how it is necessary to build population of next generation. As a rule,
probability of participation of individual in crossing undertakes to his proportional adjusted. So urgent strategy of elitism,
at which a few best individuals pass to the next generation without changes, is often used, not participating in a
crossing-over and selection. In any case, every next generation it will be on the average better previous. When the adjusted
of individuals stops to be increased, a process is stopped and as a decision of task of optimization take the best from the found
individuals.
    Going back to the task of construction of optimum plan, it is necessary to explain the features of realization
of genetic algorithm in this case:
- Individual = variant of decision of task = set from m chromosomes of Xj, where m is an amount of wares, producible an enterprise;
- A chromosome of Xj = a volume of output of products j = 16, it is a bit record of this number.
    Because the volumes of products are limited, not all values of chromosomes are possible. It is taken into account
during the generation of population. The mechanisms of crossing-over (crossings) and mutation will realize elective part, and a
selection of the best decisions is the gradient lowering.
    That, if on some great number a difficult function is set from a few the variables, then a genetic algorithm is the
program which for possible time finds a point, where a value of function is enough close to the maximally possible value. Choosing
an acceptable checkout, get the best decisions which can be got for this time.
    Stand a genetic algorithm generates initial population casual appearance. Work of genetic algorithm presents an
iteration process which proceeds until the set number of generations or any other criterion of stop will not be executed. In every
generation of genetic algorithm a selection will be realized proportionally adjusted, crossing-over and mutation.
    At first, a proportional selection appoints probability to every structure Ps(i) equal to attitude of its adjusted
toward total adjusted of population:
(4)
    Then there is a selection (with a substitution) all n individuals for further genetic treatment, according to a size Ps(i).
At such selection the members of population with high adjusted with greater probability will get out more frequent, than individuals
with low adjusted. After a selection, n select individuals broke up on casual appearance n/2 pair. For every pair with probability
Ps a crossing-over can be used. Accordingly, with probability 1–Ps a crossing-over does not take place and those individuals pass
to the stage of mutation. If a crossing-over takes place, the got descendants replace parents and pass to the mutation.
    We will define concepts now, answering mutations and to the crossing-over in a genetic algorithm.
    A crossing-over is an operation at which from two chromosomes one or a few new chromosomes are generated. One-point
crossing-over works as follows. At first, one of length–1 points of break gets out casual appearance. (A point of break is an area
between nearby bats in a line.) Both paternal structures in this point are torn on two segments. Then, the proper segments of different
parents stick together and go out two genotypes of descendants.
    Since the stage of crossing-over is closed, the operators of mutation are executed. In a line which a mutation is used to,
every bit with some probability changes on opposite. Population, got after a mutation, passes the stage of elite selection. This
method of selection guarantees it will survive the best or the best members of population of aggregate.
    Next generations are processed in like manner: selection, crossing-over and mutation.
    As it applies to our put task every individual consists of array X and values of function F on variables, extracted
from this array.
    We use in the program a genetic algorithm, consisting of the followings steps:
    1. Generation of initial population, using strategy "focus", is filling of population individuals in which array cells
X (bats) filled by casual appearance within the limits of scopes, certain an user.
    2. Choice of paternal pair by the method of roulette, i.e. method of proportional selection. Chromosomes are represented
as cutting-off of lines or sectors of roulette all the same by appearance, that their size is proportional to the value of objective
function. Further numbers casual appearance generate in an interval from 0 to 1, and those individuals get out as parents, random
numbers get in whose segment. The numbers of chromosomes of parents must differ thus.
    3. A crossing-over takes place as follows: we take a casual point t on an array X (0..length–1). After it exchange parts
of chromosomes (bats 0-t fill a new individual (descendant) the elements of the first paternal individual, and other elements are
filled from the array of the second paternal individual; for the second descendant done vice versa). Thus, we choose fourth part
of pair of parents from the initial size of population and on their basis get descendants in an amount a half from the initial size
of population. We use an one-point crossing-over. Got individuals – descendants is added to population.
    4. All individuals execute mutation with some probability – the casual bit of array is inverted X to this individual.
    5. We abbreviate intermediate population on an elite chart – the again built streams replace worst parents,
in obedience to the values of objective function.
    6. If the best decision in population dissatisfies us, then passed to the step 2.
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Description of the got and planned results
    On results for analysis of description of subsystem of planning and prognostication of issue of products:
    - specified and complemented planning principles in the conditions of indefiniteness, and also the concept of the
adaptive planning of the production program of enterprise is entered;
    - authentication of factors, which having influence on planning of issue of products on an enterprise and reflecting
of a particular branch specific is conducted;
    - entrance information, necessary for the construction of subsystem, is certain.
    Methodological basis for research was made by positions of analysis of the systems, methods of planning of the production
program of enterprise, methods of mathematical statistics, economics and mathematics methods and models, expert methods, methods of
acceptance of administrative decisions in the conditions of indefinite.
    In works of many authors the attempts of account of indefiniteness are done by the use of different methodological
approaches. Offered approaches present both scientific and practical interest. At the same time we came to the conclusion, that it
does not exist enough universal methods of forming of plan of issue of products enterprises, in which all factors, providing
efficiency of this process, would be complex taken into account.
    Unfortunately, classic methods are ineffective in many practical tasks. It is related to that it is impossible full enough
to describe reality by the small number of model parameters, or a model calculation requires too much time and calculable resources.
From the lacks of traditional methods to the last active development of the analytical systems of new type goes 10 years. In their
basis are technologies of artificial intelligence, imitating natural processes, such as activity of neurons of brain or process of
natural selection. Most popular and tested from these technologies there are neuron networks and genetic algorithms which can be used
for the decision of task of planning and forecasting of products issue on an enterprise.
    As a result of implementation of work the algorithm of work of subsystem of planning and forecasting of issue of products
was developed in the conditions of sewing enterprise join-stock company of the closed type "DOTI" (Figure 1).
    Creation of the program, which is realizing the developed algorithm of work of subsystem, is also planned in-process.
Figure 1 – Algorithm of work of subsystem of planning and forecasting of issue of products
(animation: volume – 32,286 KB; size – 710х236; amount of shots – 5; frequency of shots changing – 2000 ms; amount of repeated cycles
– a continuous cycle of reiteration)
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    At writing of this abstract of thesis master's degree work is not yet completed. Final completion:
December, 2009. Complete text of work and materials on the topic can be got for an author or his leader after the indicated date.