RU2694019C2 - Method of selecting optimal strategy in combat actions of different groups - Google Patents

Abstract

FIELD: physics.

SUBSTANCE: invention relates to digital computer engineering. Method of selecting an optimal strategy in combat actions of different groups, according to which initial data of combat means of sides A and B are recorded in a memory unit, where the initial data are supplemented with information on the A grouping of the combat means of the parties A side distribution in each B side grouping and simulating the group combat simultaneously with all enemy groups taking into account the data, performing the simulation, when using data on location of combat means of groupings, with a mark of group combat results in selected discrete time points obtained in discrete selected points as initial for the second simulation stage, determining final remains of their combat means and destroyed enemy combat means, which are displayed on the display panel.

EFFECT: high accuracy of processing information by taking into account heterogeneity of characteristics of BSr groups and selection of strategy for optimal target distribution on group objects, which leads to higher combat effectiveness (effectiveness) in group combat: destruction of enemy with minimum losses of own BSr.

1 cl, 2 dwg, 6 tbl

Description

The invention relates to digital computing, in particular to digital computing systems for processing input information about the characteristics of the combat means of the opposing sides, its transformation, choosing an effective strategy, evaluating the results of combat confrontation (victory, defeat, parity), determining its losses and inflicted on the enemy damage in the presence and absence of intelligence on the coordinates of the combat means of the opposing groups can be used by the commanding staff of the Armed Forces in CCE his learning and relearning of the command and staff exercises, and directly to the planning group fighting (DB) of diverse groups.

The known method [1-5], which reveals the dynamics of the battle and allows you to name the future winner before it. However, there is no known method of conducting combat against dissimilar groups with an assessment of its effectiveness. In the cited sources, first, the fight against the party consisting of heterogeneous groups is not considered. Secondly, the price of the achieved victory is not estimated, there is no quantitative assessment of causing maximum damage to the enemy. The third disadvantage is the existing shift of emphasis towards the ratio of the number of combat means (BSR) of the parties, without taking into account the heterogeneity of the groups and the method of choosing rational strategies for the destruction of the groups.

The technical result is to increase the level of accuracy of information processing by taking into account the heterogeneity of the characteristics of the BSR groupings and the choice of the strategy of optimal targeting by group objects, which leads to an increase in combat effectiveness (effectiveness) in a group battle: destruction of the enemy with minimal losses of their own BSR

Earlier [6–11], the authors considered group DBs, taking into account the difference in intensity of fire damage, the heterogeneity in providing the parties with intelligence about the coordinates of the BSR parties that influence the choice of rational strategies. In contrast to the known methods, an increase in the combat effectiveness (effectiveness) of group combat (GB) is carried out by:

- taking into account the heterogeneity of the BCP of the opposing parties;

- the choice of a rational strategy for maintaining GB;

- evaluation of the results of the upcoming battle before it.

Almost all approaches lead to the additional preservation of their BSW by the results of the DB by party A, based on the choice of a rational strategy. Let us consider a new type of heterogeneity, associated with an increase in the number of BSB groupings, to which the previous approaches [6-11] did not give effective use. Increasing the number of BSB requires the development of a new DB method with finding the optimal strategy.

According to the invention, this problem is solved by choosing the optimal strategy for defeating heterogeneous groups in such a way that the source data on the values of the indicators of its combat assets and means of each enemy grouping is commuted, recorded in a memory unit, characterized in that it is supplemented with information on the distribution of the relative number _i means of combat the A side for firing, each of which is determined by the product of the number N _i i means of combat enemy forces, multiplied by the intensity ognevog lesion λ _i of the groups divided by the total sum ΣN _i * λ _i of all works _{r i = N i * λ i} / ΣN i * λ i, calculated relative contributions r _i * M allocated combat means of side A and carried modeling group battle simultaneously with all enemy groupings, the intermediate results of the remnants of the combat means of the parties obtained at selected discrete time points are stored; for each discrete time point with a set of initial simulation results, secondary modeling is carried out with fixation of final results remnants of its combat vehicles and combat weapons of destroyed enemy, which displays on the scoreboard display.

The essence of the proposed method is to consider a bilateral fight with heterogeneous groups, when side A has one group, and the opposing party B includes three groups B _1, B _2, B ₃ . Indicators BSA side A before the start of group combat (GB) will be:

M - the initial number of military equipment of side A;

μ ₁ , μ ₂ , μ ₃ - intensity of the striking fire (IEP) BSR when firing at groups B ₁ , B ₂ , B ₃ ;

m (t) is the decreasing value of M in the database process at time t;

N ₁ , λ ₁ , n ₁ (t); N ₂ , λ ₂ , n ₂ (t); N ₃ , λ ₃ , n ₃ (t) - similar indicators of groups В ₁ В ₂ , В ₃ . Sides A, B do not have information about the coordinates of the BSR enemy groupings.

Database strategies and their classification are considered by the authors in earlier patents [6-11]. Rational management of GB, firstly, leads to the maximization of the damage caused to the enemy, and secondly, to minimize their losses.

We show that the addition of the third grouping not only leads to a quantitative, but also a qualitative change in the management of GB. Illustrative source data of the opposing groups are given in Table. one.

Consider a database with a selection of known strategies for a database with three groupings:

1. The phased results of the alternate destruction of groups in the sequence: B _1, B ₂ , B ₃ are shown in Table. 2. The end result was the defeat of the side А М _∞ (t ₃ ) = 0 (rows 2, 3, column 4), with the remainder of the BS side B In N _∞ (t ₃ ) = 12 (rows 4, 5, column 4).

2. Simultaneous destruction at the first stage of 2 groups B ₁ , B ₂ , at the second - B ₃ . The end result was the defeat of side B N _∞ (t ₂ ) = 0 (Table 3, lines 4, 5, column 3), with the remainder of the side AU M _∞ (t ₁₂ , ₃ ) = 20 (Table 3, line 2 3 column 3).

3. The results of the simultaneous destruction of the three groups B _1, B ₂ , B ₃ are given in table. 3, from which it can be seen that side A won (Table 3, lines 2, 3, column 4) with the remainder BSr M _∞ (t ₁₂₃ ) = 32.

Analysis of the results of tables 2, 3 necessitates the development of a new, more effective (optimal) strategy.

4. According to table. 1, we calculate the relative intensity flows of the fire of the three groups B ₁ , B ₂ , B ₃ according to the formulas:

5. Create the differential equations of one-step databases. With strategy S _0, a one-stage battle is conducted with the groups B _1, B ₂ , B ₃ . Differential equations reflecting the database in time t in the absence of information about the coordinates of the BSB at side A, will be written in the form:

The absence, the presence of information from the party B about the coordinates of the BS of side A is expressed in the disclosure of the values of R _B.

R _B = 1 - in the presence of intelligence at the side B about the coordinates of the BS of side A;

R _B = m (t) / M - in the absence of intelligence at the side B about the coordinates of the BSR side A.

The original data of the groups are displayed in the table. 1. Consider the situation when each of the parties does not have information about the coordinates of the opposing grouping BSR.

, с которой после уточнения, начнем второй этап моделирования с другими значениями r_i.6. First we define the starting point.

with which, after refinement, we will begin the second stage of modeling with different values of r _i .

, как показано в табл. 4, строки 1-5 со значениями r₁=0.446; r₂=0.315; r₃=0.239, рассчитанными по формулам (1а).To do this, we fix their results, i.e. the values of m (t _i ), n ₁ (t _i ), n ₂ (t _i ), n ₃ (t _i ) at time points t _i ,

, as shown in the table. 4, lines 1-5 with the values of r ₁ = 0.446; r ₂ = 0.315; r ₃ = 0.239, calculated by formulas (1a).

получаем наивысшее значение остатков БСр у стороны А М_∞(t_i)=37.Perform secondary modeling of the database on the source data of the first 5 rows of the table. 4, with the entry of the results for each column in the last 6th row. The results of the 6th row show that with

we obtain the highest value of the BSB residues at the side A M _∞ (t _i ) = 37.

путем превращения дискретных значений t_i в аналоговые. Итак, запишем строки 1 и 6, табл. 47. Specify the discrete values of the residuals M _∞ (t _i ),

by converting discrete values of t _i to analog. So, we will write lines 1 and 6, tab. four

t _i = {0.5, 1, 2, 3, 4, 5, 6},

M _∞ = {31.624, 31.8, 35.01, 36.282, 36.882, 36.922, 36.78}

pair by pair, getting the argument in the first place, in the second - the function

data: = {0.5, 31.624}, {1, 32.8}, {2.35.01}, {3, 36.28}, {4, 36.88}, {5, 36.92}, {6, 36.78}}.

By approximating existing pairs using a power function

M [t] = Fit [data , {31.624, t, t ∧ 2, t ^∧ 3, t ^∧ 4, t ^∧ 5,}, t],

we obtain an analog function of the power type:

M _∞ [t] = 30.568 + 1.775t + 0. 8476t ² -0.4367t ³ + 0.0674t ⁴ -0.0036t ⁵ ,

search for the maximum of which

FindMaximum [M _{∞ [t] = 30.568 + 1.775t} + 0.8476t ² -0. 4367t + 0.0674t ^{3 4 5} -0.0036t, {t, 5}]

produces the result {M _∞ = 36.927, {t * → 4.743}}.

The graph of the function M _∞ (t) is shown in FIG. 2. Comparison of the residuals of side A after the database using a rational strategy (Table 3) with M _∞ = 32 and proposed by the authors — optimal with M _∞ = 37, speaks of its superiority by 16%.

Consider the situation with even worse state of party A, when it does not have information about the coordinates of all 3 opposing groups B ₁ B ₂ , B ₃ , and side B - has information about the coordinates of the BSR side A. Not repeating the details of the previous review , we will focus on the main final results of this situation.

In tab. 2a shows the results of losing side A: 1) after the sequential destruction of only the group B ₁ (Table 2a, column 2);

2) after the simultaneous destruction of the groups B ₁ , B ₂ , (Table 2a, column 3);

3) after the simultaneous destruction of groups B ₁ , B ₂ , B ₃ (Table 2a, column 4).

In tab. 3a shows the results of the database due to the application of the optimal strategy S _o ^* , determined in the same way as the first situation, when both sides did not have intelligence information about the BS coordinates of the opposing sides. From tab. 2a, 3a, it can be seen that side A can win the battle only by using the optimal strategy.

So, the proposed method allows to obtain the claimed technical result of increasing the level of accuracy of information processing by taking into account the heterogeneity of the characteristics of the BSR groupings and the choice of the strategy of optimal targeting by group objects, which leads to the destruction of the enemy with minimal losses of their own BSR.

The decision of the authors of various examples for groupings with different initial data revealed:

- the ability to control the outcome of the database without resorting to the development of new BSBs, which requires large financial and time costs, and without using a quantitative build-up of the BSBs, which is not always feasible and expeditiously feasible;

- the need to model various types of group heterogeneity, their competent accounting with the possibility of choosing the optimal strategy allows you to quickly and without additional costs to achieve the desired result.

To implement the proposed method is possible, at the first stage, with the help of a computer, at the second, in the form of a programmed device.

Used sources

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Claims (1)

The method of selecting the optimal strategy in the hostilities of heterogeneous groups, according to which the initial data of the combat means of sides A and B are recorded in a memory block, characterized in that the initial data supplement the information on the distribution of the combat means of grouping sides A for each grouping side B simultaneously with all enemy groupings, taking into account the data, when each side does not have information about the coordinates of the combat means, carry out simulations when using data about the location of group combat equipment, with a mark of group battle results at selected discrete time points, obtained at discrete designated points as initial for the second modeling stage, determine the final remnants of their combat vehicles and destroyed enemy weapons, which are displayed on the display board.

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