CN1845156A - Command control method of rapid deployment for war field mechanization infantry - Google Patents

Abstract

The invention relates to a quick command control method for quickly low-risk deploying mechanization infantry on the battlefield. Wherein, the commanded object the all mechanization infantries; according to the lengths from different concentrate points to different deploy points, the transmission non-baffle probability, the deploy amount at the concentrate point, the needed amount at the deploy point, and the speed and load of transmission device, the command control mode purposed for transmitting all infantries in minimum time is built; and using linear programming, and the pair rule of linear programming, to solve said mode, and improve the result via the two-dimension table, to obtain the command control method that meeting the demand of quick deploy time. The invention can improve the battle effectiveness, with wider application. The invention also provides relative technique.

Description

Commander's control method that a kind of battlefield mechanized infantry disposes fast

Technical field the present invention relates to national defence and association area, is used for the battlefield mechanized infantry is disposed enforcement commander control fast, realizes the quick deployment to the battlefield mechanized infantry.

Background technology is implemented quick mechanized infantry's transportation between battlefield mechanized infantry's assembly place and deployment point commander's control is an important component part of operational commanding control, length according to mechanized infantry's transportation route from different assembly places to different deployment points, the without hindrance transportation probability of transportation route, the assembly place infantry can the deployment amount and the deployment point to infantry's demand, the speed of means of transport and carrying capacity, structure is that commander's control plan of target is that the battlefield commander disposes fast the battlefield mechanized infantry and implements the key issue that commander's control must solve to transport all infantries minimum that expends time in, the solution of this problem is for increasing substantially fighting capacity, minimizing has crucial meaning to the demand of deployment mechanized infantry's means of transport.

Mobile operations are most important for the triumph of capturing IT-based warfare, complicated battlefield surroundings may impact the traffic capacity of the transportation route of disposing the mechanized infantry, thereby reduce the passage rate of means of transport, and commander's control of disposing the mechanized infantry between combat division or trip and the subordinate fast is the key that improves mobile operations, and wherein the matter of utmost importance that must solve is commander's control plan of the deployment mechanized infantry of formulation science.The quality of this plan, not only be related to implement the battlefield mechanized infantry dispose the transport resource that consumes how much, can in time arrive the deployment point but also be related to the mechanized infantry, to guarantee that fighting capacity is unlikely to descend because of the delay that the mechanized infantry transports.

For the battlefield mechanized infantry dispose and commander's control of this deployments the time seem more important, therefore must by antithesis analyze the choose reasonable parameter improve solvability and with deployment time minimum come the battlefield mechanized infantry disposed to implement to command fast to control as optimization aim.

The present invention relates to commander's control method that the battlefield mechanized infantry disposes fast, relate to military affairs and association area, the object of commander's control is all battlefield mechanized infantries, this method is according to the length of the mechanized infantry's transportation route from different assembly places to different deployment points, the without hindrance transportation probability of transportation route, the assembly place infantry can the deployment amount and the deployment point to infantry's demand, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all infantries minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model, by two-dimentional form solving result is updated again, meet the option control command that quick deployment time requires until final acquisition, this method has efficiently, simply, objective, characteristics are widely used and obviously improve its combat capabilities etc., can be widely used in commander's control that all battlefield mechanized infantries dispose fast, the invention further relates to the technology that realizes this method.

Summary of the invention the present invention is according to the length of the mechanized infantry's transportation route from different assembly places to different deployment points, the without hindrance transportation probability of transportation route, the assembly place infantry can the deployment amount and the deployment point to infantry's demand, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all infantries minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model, obtain to implement to command the scheme of controlling with two-dimentional form description the battlefield mechanized infantry is disposed fast, and check whether this option control command meets the time demand of finishing whole battlefield mechanized infantry's deployment task, if do not meet the demands, then by analysis to this two dimension commander control form, and according to shadow price, the time bottleneck can be adjusted for the mechanized infantry's quantity of deployment and the means of transport of enforcement deployment etc. the relevant episode node, constantly repeat this and find the solution-check analytic process, meet the option control command that the battlefield mechanized infantry requires quick deployment time until final acquisition.Therefore, the battlefield mechanized infantry conception of commander's control of deployment is fast proposed, introduce the analytical approach of the without hindrance transportation probability of transportation route, set up linear programming and the dual program model of seeking optimum option control command, by finding the solution this model, obtain to implement to command the scheme of controlling with two-dimentional form description the battlefield mechanized infantry is disposed fast, and according to finishing the time requirement that whole mechanized infantry disposes, by searching the time bottleneck that whole battlefield mechanized infantry's deployment task is finished in influence, the assembly place can be adjusted for the unreasonable configuration of mechanized infantry's quantity of disposing with to the means of transport of implementing to dispose, continue to optimize and improve this option control command, and the final time requirement that obtains to satisfy the quick deployment of battlefield mechanized infantry, option control command with two-dimentional form description becomes key character of the present invention.

The technical scheme of commander's control method that a kind of battlefield mechanized infantry of the present invention disposes fast is:

At first, the quick deployment issue of battlefield mechanized infantry is defined as the supply and demand system that the party in request (deployment point) by mechanized infantry's supplier (assembly place) and mechanized infantry is constituted, the feature of this system can be used the length of the transportation route of disposing from different suppliers to the different mechanized infantries of party in request, the without hindrance transportation probability of transportation route, supplier mechanized infantry's supply and the mechanized infantry's of party in request demand, the speed and the carrying capacity of means of transport are described, and according to the time requirement that the battlefield mechanized infantry is disposed, structure is commander's controlling models of target to dispose and to transport all mechanized infantries minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model, obtain to implement to command the scheme of controlling with two-dimentional form description the battlefield mechanized infantry is disposed fast, time bottleneck by continuous searching supply and demand system, quantity to relevant supplier's mechanized infantry is carried out reasonable disposition, adopt methods such as different means of transports, the final time requirement that obtains to satisfy the quick deployment of battlefield mechanized infantry, the battlefield mechanized infantry is disposed the scheme of implementing commander's control fast, finish commander's control that the battlefield mechanized infantry is disposed fast.

The traffic capacity of the transportation route that complicated battlefield surroundings may be disposed the mechanized infantry impacts, thereby reduce the passage rate of means of transport, for being the commander control of target to transport mechanized infantry's minimum that expends time in, this reduction has been equivalent to increase the length of transportation route, transportation route length after claiming to increase is equivalent path length, introduced the without hindrance transportation probability of transportation route and solved relevant issues in order to consider this influence, the without hindrance transportation probability of transportation route is with the function of time as variable, equivalent transportation route length then is with the function of the without hindrance transportation probability of actual shipment path and relevant transportation route as variable, when the without hindrance transportation probability of transportation route is 1, actual shipment path and equivalent transportation route equal in length, and the without hindrance transportation probability of transportation route is more little, and then compare equivalent transportation route length with the actual shipment path just long more.

Usually, the target of the objective function of commander's controlling models is for making deployment and transporting all mechanized infantries minimum that expends time in, but when the without hindrance transportation probability of the transportation route in all paths was 1, the target of the objective function of this commander's controlling models was simultaneously also for making deployment and transport all mechanized infantries the carrying capacity that needs to be minimum.

Find the solution commander's controlling models by the method for finding the solution linear programming and finding the solution the dual program of linear programming, can obtain respectively to dispose and transport the minimum time that the mechanized infantry needs to different parties in request from different suppliers, the shadow price relevant with different parties in request constraint condition with different suppliers, the result that will find the solution inserts in a kind of two dimension commander's control form again, by analysis to this form, and according to shadow price, the time bottleneck is adjusted correlation parameter, constantly find the solution and update, can finally obtain to meet the option control command that the battlefield mechanized infantry requires quick deployment time.

Can describe the quantity of disposing and transporting the mechanized infantry from each supplier to each party in request, the size that each party in request needs transport power, the quantity of means of transport, the minimum time and relevant shadow price that transportation expends by the zones of different in the two dimension commander control form, the situation of change of quantity, residue mechanized infantry quantity that each supplier supplies the mechanized infantry is with relevant shadow price and deployment and transport the minimum time that all mechanized infantries expend.

If the option control command of trying to achieve can not satisfy the preset time requirement, then can be by two dimension commander control table, result to former linear programming and dual program analyzes, determine to influence the bottleneck that the battlefield mechanized infantry disposes T.T., again by supplier's mechanized infantry's quantity being carried out reasonable disposition, increasing the quantity of means of transport and adopt different means such as means of transport, eliminate the time bottleneck, and repeat this process, until making the predetermined requirement that meets T.T. of finishing battlefield mechanized infantry deployment and transportation.

Commander's control method that the battlefield mechanized infantry of the present invention's design disposes fast is applicable to that it is key character of the present invention that all battlefield mechanized infantries dispose fast.

The case study of commander's control that the battlefield mechanized infantry disposes fast is as follows.

Supposing that the quick deployment issue of battlefield mechanized infantry can be used by m supply mechanized infantry's assembly place and n demand mechanized infantry's deployment point and between different supply and demand nodes exists the network in a Transport Machinery infantry's path to describe, and is x from supplying mechanized infantry's quantity that node i transports to demand node j _Ij, the without hindrance transportation probability of transportation route is p _Ij(t), the physical length of transportation route is r _Ij, the equivalent length of transportation route is d _IjThe without hindrance transportation probability of transportation route is meant that complicated battlefield surroundings may impact the traffic capacity of mechanized infantry's transportation route, thereby reduce the passage rate of means of transport, for being the commander control of target to transport mechanized infantry's minimum that expends time in, this reduction has been equivalent to increase the length of transportation route, transportation route length after claiming to increase is equivalent path length, the without hindrance transportation probability of transportation route is with the function of time as variable, equivalent transportation route length then is with the function of the without hindrance transportation probability of actual shipment path and relevant transportation route as variable, when the without hindrance transportation probability of transportation route is 1, actual shipment path and equivalent transportation route equal in length.

The problem that need to solve is that one of design is transported the mechanized infantry to n deployment point from m assembly place, make the carrying capacity and the consumed time of transporting all mechanized infantry's costs be minimum movement plan simultaneously, and calculate the quantity that the required means of transport of mechanized infantry is transported in each assembly place, it is as follows that relevant mechanized infantry disposes commander controlling models and linear programming equation:

Objective function: $\min Z=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{d}_{\mathrm{ij}}{x}_{\mathrm{ij}}$

The deployment point demand equals constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{ie}}=D_e,$ (e＝1，…，n _e)

The deployment point demand is less than constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{il}}\≤D_l,$ (l＝n _e+1，…，n _l)

The deployment point demand is greater than constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{is}}\≥D_s,$ (s＝n _l+1，…，n _s)

The assembly place supply equals constraint condition: $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ej}}=S_e,$ (e＝n _s+1，…，m _e)

The assembly place supply is less than constraint condition: $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{lj}}\≤S_l,$ (l＝m _e+1，…，m _l)

The assembly place is in large supply in constraint condition: $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{sj}}\≥S_s,$ (s＝m _l+1，…，m _s)

Condition of Non-Negative Constrains: x _Ij〉=0, (i=1 ..., m; J=1 ..., n)

The classification of the amount relevant with the deployment point Demand Constraint: $D_v=\left\{\begin{array}{c}{D}_e,(1\≤v\≤n_e)\\ D_l,(n_e+1\≤v\≤n_l)\\ D_s,(n_l+1\≤v\≤n_s)\end{array}\right.$

The classification of the amount relevant with assembly place supply constraint: $S_u=\left\{\begin{array}{c}{S}_e,(n_s+1\≤u\≤m_e)\\ S_l,(m_e+1\≤u\≤m_l)\\ S_s,(m_l+1\≤u\≤m_s)\end{array}\right.$

The equivalent length of transportation route is: d _Ij=f (r _Ij, p _Ij(t)), (0＜p _Ij(t)≤1; I=1 ..., m; J=1 ..., n) assembly place i (i=1 ... m) the means of transport quantity V of Xu Yaoing _i:

From assembly place i (i=1 ... m) transport the mechanized infantry to deployment point j (j=1 ... n) spent time: $T_{\mathrm{ij}}=\frac{d_{\mathrm{ij}}}{C}$

Finish all mechanized infantries and dispose spent minimum time: minT=max{T _Ij}

Wherein:

M is supply mechanized infantry's assembly place sum;

N is demand mechanized infantry's a deployment point sum;

r _IjFor assembly place i (i=1 ... m) with deployment point j (j=1 ... the physical length of the transportation route n) (unit: kilometer);

p _Ij(t) be assembly place i (i=1 ... m) with deployment point j (j=1 ... n) the without hindrance transportation probability of the transportation route between is with the function of time t as variable;

d _IjFor assembly place i (i=1 ... m) with deployment point j (j=1 ... the equivalent length of the transportation route n) (unit: kilometer), work as p _Ij(t)=1 o'clock, r _IjWith d _IjEquate;

E is the sequence number that equals the amount of equaling of constraint condition;

L is the sequence number less than the constraint condition upper limit;

S is the sequence number greater than the constraint condition lower limit;

n _eMaximum sequence number for the equal amount that equal constraint condition relevant with the deployment point demand;

n _lBe the maximum sequence number less than the constraint condition upper limit relevant with the deployment point demand;

n _sBe the maximum sequence number greater than constraint condition lower limit relevant with the deployment point demand;

D _eFor with the deployment point need the relevant amount of mechanized infantry's quantity (e=1 ..., n _e) (unit: the people);

D _lFor needing the relevant upper limit (l=n of mechanized infantry's quantity with the deployment point _e+ 1 ..., n _l) (unit: the people);

D _sFor needing the relevant lower limit (s=n of mechanized infantry's quantity with the deployment point _l+ 1 ..., n _s) (unit: the people);

m _eMaximum sequence number for the equal amount that equal constraint condition relevant with the assembly place supply;

m _lBe the maximum sequence number less than the constraint condition upper limit relevant with the assembly place supply;

m _sBe the maximum sequence number greater than constraint condition lower limit relevant with the assembly place supply;

S _eFor supplying mechanized infantry's the relevant amount (e=n of quantity with the assembly place _s+ 1 ..., m _e) (unit: the people);

S _lFor supplying mechanized infantry's quantity the relevant upper limit (l=m with the assembly place _e+ 1 ..., m _l) (unit: the people);

S _sFor supplying mechanized infantry's quantity relevant lower limit (s=m with the assembly place _l+ 1 ..., m _s) (unit: the people);

V _iFor the supply mechanized infantry assembly place i (i=1 ... m) transport the means of transport quantity that the mechanized infantry needs;

L transports mechanized infantry's ability (unit: the people) for each means of transport;

C transports mechanized infantry's speed (unit: kilometer/hour) for each means of transport;

Above-mentioned model shows: try to achieve by linear programming on the basis of minZ value, can calculate mechanized infantry's quantity x that each assembly place must be transported to the related deployment point _Ij,, can calculate the means of transport quantity V that each assembly place needs again according to the dead weight capacity L of means of transport _iTransport mechanized infantry's speed C and the longest path between assembly place and deployment point at last according to means of transport, can calculate again and finish the spent shortest time T of whole mechanized infantry's deployment task, thereby realize that the commander that the battlefield mechanized infantry is disposed fast controls, for constraint condition rationally being set, improving solvability, utilizing above-mentioned linear programming model better, the dual linear programming model that provides this model is as follows:

Objective function: $\max G=\underset{v=1}{\overset{n_e}{\mathrm{\Σ}}}{D}_v{y}_v+\underset{v=n_e+1}{\overset{n_l}{\mathrm{\Σ}}}{D}_v{y}_v+\underset{v=n_l+1}{\overset{n_s}{\mathrm{\Σ}}}{D}_v{y}_v+\underset{u=n_s+1}{\overset{m_e}{\mathrm{\Σ}}}{S}_u{y}_u+\underset{u=m_e+1}{\overset{m_l}{\mathrm{\Σ}}}{S}_u{y}_u+\underset{u=m_l+1}{\overset{m_s}{\mathrm{\Σ}}}{S}_u{y}_u$

Constraint condition: $D_e{y}_{n_e\left(j\right)}+D_l{y}_{n_l\left(j\right)}+D_s{y}_{n_s\left(j\right)}+S_e{y}_{m_e\left(i\right)}+S_l{y}_{m_l\left(i\right)}+S_s{y}_{m_s\left(i\right)}\≤d_{\mathrm{ij}}(i=1,\·\·\·,m;j=1,\·\·\·,n)$

Condition of Non-Negative Constrains: $y_{m_l\left(i\right)},y_{n_l\left(j\right)}\≤0(i=1,\·\·\·,m;j=1,\·\·\·,n)$

Non-positive constraint condition: $y_{m_s\left(i\right)},y_{n_s\left(j\right)}\≥0(i=1,\·\·\·,m;j=1,\·\·\·,n)$

Wherein:

$y_{n_e\left(j\right)}=y_v(1\≤v{\≤n}_e),y_{n_l\left(j\right)}=y_v(n_e+1\≤v{\≤n}_l),y_{n_s\left(j\right)}=y_v(n_l+1\≤v{\≤n}_s)$ Be the variable subscript sequence number transforming function transformation function relevant with j;

$y_{m_e\left(i\right)}=y_u(n_s+1\≤u{\≤m}_e),y_{m_l\left(i\right)}=y_u(m_e+1\≤u{\≤m}_l),y_{m_s\left(i\right)}=y_u(m_l+1\≤u{\≤m}_s)$ Be the variable subscript sequence number transforming function transformation function relevant with i;

y _v, y _u(v=1 ..., n _sU=n _s+ 1 ..., m _s) be respectively the relevant decision variable of shadow price with the demand of former linear programming and supply mechanized infantry constraint condition;

Since primal linear programming solves be with deployment point j and assembly place i (i=1 ..., m; J=1 ..., the resource optimal utilization problem that constraint condition n) is relevant, thus dual program solve then be estimate to make deployment point j and assembly place i (i=1 ..., m; J=1 ..., constraint condition n) satisfies the cost problem that must pay, promptly uses the valency problem, and shadow price y _vAnd y _uReflection make just deployment point j and assembly place i (i=1 ..., m; J=1, n) constraint condition satisfies the cost that must pay, minimizes (or maximization) by making the target function value relevant with cost, and shadow price can be used for each constraint condition of comparison and carry out equivalence analysis to the contribution of target function value or to this contribution influence.The implication of a certain constraint condition shadow price is when the constant of its pairing constraint condition right-hand member increases a unit, the numerical value that former problem objective function optimal value increases.Shadow price is big more, shows that this constraint condition is big more to the influence of the minimum delivery power of option control command, and the difficulty that satisfies this condition is big more.Therefore, by comparing shadow price and realistic objective functional value, can the variation that can study former linear programming constraint condition make objective function obtain gain.

Embodiment

Implementation example

In IT-based warfare, the mechanized infantry's of mechanization combat division deployment ability is an important component part of its fighting capacity, to huge battlefield mechanized infantry's deployment and the demand of transporting power and time, make commander's control of implementing battlefield mechanized infantry deployment become vital task, suppose that certain mechanization combat division must be 16 people with dead weight capacity, average speed per hour is 70 kilometers a armored personnel carrier, transport the mechanized infantry of specified amount to 14 deployment points from 6 assembly places, transportation route length between assembly place and the deployment point, the assembly place infantry can the deployment amount and the deployment point as shown in table 1 to the bound of infantry's demand, make the without hindrance transportation Probability p of all transportation routes here _Ij(t) be 1, d _Ij=r _Ij/ p _iJ (t), therefore actual shipment path and equivalent transportation route equal in length, the i.e. r between different supply and demand sides _IjWith d _IjEquate.

Table 1: transportation route length and portion's amount of asking between mechanization combat division assembly place and the deployment point (unit: axiom, people)

	01 assembly place	02 assembly place	03 assembly place	04 assembly place	05 assembly place	06 assembly place	The demand upper limit	The demand lower limit
									14 deployment points, 13 deployment points, 12 deployment points, 11 deployment points, 10 deployment points, 09 deployment point, 08 deployment point, 07 deployment point, 06 deployment point, 05 deployment point, 04 deployment point, 03 deployment point, 02 deployment point, 01 deployment point	37.00 34.00 25.00 14.00 26.00 24.00 120.00 159.00 112.00 62.00 91.00 126.00 90.00 81.00	13.00 25.00 28.00 15.00 35.00 20.00 98.00 138.00 96.00 37.00 66.00 97.00 68.00 56.00	70.00 83.00 108.00 97.00 82.00 110.00 12.00 51.00 96.00 46.00 17.00 81.00 99.00 20.00	74.00 87.00 112.00 101.00 86.00 100.00 129.00 149.00 25.00 50.00 79.00 86.00 104.00 66.00	44.00 31.00 66.00 58.00 56.00 39.00 105.00 145.00 110.00 59.00 73.00 27.00 11.00 75.00	60.00 19.00 56.00 30.00 48.00 65.00 75.00 30.00 69.00 70.00 26.00 65.00 72.00 44.00	36.00 21.00 90.00 130.00 70.00 40.00 60.00 16.00 29.00 36.00 90.00 30.00 35.00 28.00	36.00 21.00 90.00 130.00 70.00 10.00 60.00 16.00 29.00 36.00 80.00 20.00 25.00 22.00
Can keep supplying limit	100.00	200.00	300.00	400.00	150.00	350.00
									Can supply lower limit	100.00	60.00	40.00	10.00	10.00	20.00

According to above-mentioned linear programming and commander controlling models and relevant dual linear programming model, the option control command that the minimum time mechanized infantry of mechanization combat division who calculates by simplex algorithm disposes is as shown in table 2,

Table 2: mechanization combat division minimum time is disposed option control command (unit: people, passenger-kilometer,, minute)

	01 assembly place	02 assembly place	03 assembly place	04 assembly place	05 assembly place	06 assembly place	Ton kilometre	The truck number	Need the time	Upper limit shadow valency	Lower limit shadow valency
												14 deployment points, 13 deployment points, 12 deployment points, 11 deployment points, 10 deployment points, 09 deployment point, 08 deployment point, 07 deployment point, 06 deployment point, 05 deployment point, 04 deployment point, 03 deployment point, 02 deployment point, 01 deployment point	30.00 70.00	36.00 60.00 64.00 40.00	60.00 36.00 80.00 22.00	29.00	20.00 25.00	21.00 66.00 16.00	468.00 399.00 2430.00 2940.00 1820.00 800.00 720.00 480.00 725.00 1656.00 1360.00 540.00 275.00 440.00	3 2 6 9 5 3 4 1 2 3 5 2 2 2	11.14 16.29 24.00 25.71 22.29 17.14 10.29 25.71 21.43 39.43 14.57 23.14 9.43 17.14	13.00 19.00 25.00 14.00 26.00 20.00 12.00 30.00 25.00 37.00 0.00 0.00 0.00 0.00	13.00 19.00 25.00 14.00 26.00 20.00 12.00 30.00 25.00 37.00 17.00 27.00 11.00 20.00
Add up to	100.00	200.00	198.00	29.00	45.00	103.00	15053.00	49	39.43 *
												Quantity available	100.00	200.00	300.00	400.00	150.00	350.00
For the back surplus	0.00	0.00	102.00	371.00	105.00	247.00
												Upper limit shadow valency	0.00	0.00	0.00	0.00	0.00	0.00
Lower limit shadow valency	0.00	0.00	0.00	0.00	0.00	0.00

* finish the minimum time that deployment task needs

By option control command (table 2) is analyzed as can be known; it is 39.43 minutes that the armored personnel carrier that finishing deployment task needs adds up to 49, time; the armored personnel carrier that 01～06 assembly place needs is respectively 11,16,14,2,4 and 12, therefore must implement to lay special stress on protecting to 02,03 and 06 assembly place.Further analyze as can be known, transporting 36 39.43 minutes that the mechanized infantry spent from 03 assembly place to 10 deployment points is bottlenecks that the whole deployment task of restriction is finished sooner, if finish this part mechanized infantry's transportation with helicopter, then can be shortened to 25.71 minutes the time of finishing whole deployment task, reduction is 34.80%.

From to demand constraint condition D _v(v=1,18) analysis of shadow price as can be known, the size of price has truly reflected the complexity that the related constraint condition satisfies, shadow price is meant in specific span for " 0 ", relevant constraint condition does not constitute influence to target function value, the easiest to be satisfied, promptly this resource is not in short supply, if increase this resource again the optimal value of objective function is further reduced, again for example, in order to satisfy constraint condition D ₁₀, transported the mechanized infantry 39.43 minutes consuming time to 10 deployment points, the shadow price of this constraint condition is a maximal value 37, illustrates that this condition is the most difficult satisfied, can be by D with similar method _vThe complexity that satisfies, from difficulty to easy ordering: D ₁₀, D ₈, D ₁₆, D ₅, D ₃, D ₉...From to supply constraint condition S _u(u=19 ..., 29) analysis of shadow price as can be known, their shadow price is " 0 ".Therefore, in specific span, change S _uValue target function value is not constituted influence.Must be pointed out that shadow price is not changeless, can be along with D _vAnd S _uVariation and change, make the resource that does not originally constitute influence become influential resource.By analysis to shadow price, can adjust constraint condition targetedly, reach the purpose that reduces carrying capacity and haulage time.Because shadow price is the result who obtains under specific constraint condition, only in its valid interval, price just has relative stability.

Measure as can be seen from the residue mechanized infantry of each assembly place, back of finishing the work, the mechanized infantry of 02 assembly place exhausts, obviously on the low side, and that the mechanized infantry of 04 assembly place measures is obviously bigger than normal, and according to the antithesis analysis, the shadow price of their constraint condition is " 0 ", this statement of facts: if there is more mechanized infantry 02 assembly place, there is mechanized infantry still less 04 assembly place, just may obtain better to map out the plan, so adjust the upper limit S of constraint condition targetedly ₂₅Be increased to 400 from 200, make S simultaneously ₂₇Reduce to 200 from 400, the improvement project that the mechanization combat division minimum time of obtaining is disposed is as shown in table 3,

Table 3: mechanization combat division minimum time is disposed the improvement project (unit: people, passenger-kilometer,, minute) of commander's control

	01 assembly place	02 assembly place	03 assembly place	04 assembly place	05 assembly place	06 assembly place	Ton kilometre	The truck number	Need the time	Upper limit shadow valency	Lower limit shadow valency
												14 deployment points, 13 deployment points, 12 deployment points, 11 deployment points, 10 deployment points, 09 deployment point, 08 deployment point, 07 deployment point, 06 deployment point, 05 deployment point, 04 deployment point, 03 deployment point, 02 deployment point, 01 deployment point	30.00 70.00	36.00 60.00 130.00 40.00 36.00	60.00 80.00 22	29.00	20.00 25.00	21.00 16.00	468.00 399.00 2430.00 1950.00 1820.00 800.00 720.00 480.00 725.00 1332.00 1360.00 540.00 275.00 440.00	3 2 6 9 5 3 4 1 2 3 5 2 2 2 2	11.14 16.29 24.00 12.86 22.29 17.14 10.29 25.71 21.43 31.71 14.57 23.14 9.43 17.14	13.00 19.00 25.00 14.00 26.00 20.00 12.00 30.00 25.00 37.00 0.00 0.00 0.00 0.00	13.00 19.00 25.00 11.00 26.00 20.00 12.00 30.00 25.00 37.00 17.00 27.00 11.00 20.00
Add up to	100.00	302.00	162.00	29.00	45.00	37.00	13739.00	49	31.71 *
												Quantity available	100.00	400.00	300.00	200.00	150.00	350.00
For the back surplus	0.00	98.00	138.00	171.00	105.00	313.00
												Upper limit shadow valency	0.00	0.00	0.00	0.00	0.00	0.00
Lower limit shadow valency	0.00	0.00	0.00	0.00	0.00	0.00

* finish the minimum time that deployment task needs

Analysis by his-and-hers watches 3 as can be known, the time that finishing deployment task needs shortens to 31.71 minutes, amount of decrease is 19.58%, total carrying capacity is reduced to 13739 passenger-kilometers, and amount of decrease is 8.73%, and antithesis the analysis showed that: shadow price is without any variation, but the scheme after improving is better, therefore, can also carry out reasonable configuration to the mechanized infantry of each assembly place with said method, realization can be disposed the Optimal Management of mechanized infantry's quantity.

Claims (9)

1, the present invention relates to commander's control method that the battlefield mechanized infantry disposes fast, relate to military affairs and association area, the object of commander's control is all battlefield mechanized infantries, this method is according to the length of the mechanized infantry's transportation route from different assembly places to different deployment points, the without hindrance transportation probability of transportation route, the assembly place infantry can the deployment amount and the deployment point to infantry's demand, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all infantries minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model, by two-dimentional form solving result is updated again, meet the option control command that quick deployment time requires until final acquisition, this scheme is applicable to commander's control that all battlefield mechanized infantries dispose fast.

2, the quick commander's control method of disposing of battlefield mechanized infantry according to claim 1, the object that it is characterized in that described commander's control is meant the object as commander's control with all battlefield mechanized infantries for all battlefield mechanized infantries, described commander's control is meant according to the actual demand of battlefield to the mechanized infantry, design is transported to different deployment points with the battlefield mechanized infantry from different assembly places, and make total haulage time of needing or total movement capacity for minimum, can be for the scheme of implementing.

3, the quick commander's control method of disposing of battlefield mechanized infantry according to claim 1, it is characterized in that described this method according to the without hindrance transportation probability of length, transportation route of mechanized infantry's transportation route, assembly place infantry from different assembly places to different deployment points can the deployment amount and the deployment point speed of infantry's demand, means of transport and carrying capacity are meant by these parameters can set up the supply and demand system that a battlefield mechanized infantry disposes, obtain on this basis the battlefield mechanized infantry is disposed the method for implementing commander's control.

4, commander's control method that battlefield mechanized infantry according to claim 1 disposes fast, it is characterized in that the without hindrance transportation probability of described transportation route is meant that complicated battlefield surroundings may impact the traffic capacity of mechanized infantry's transportation route, thereby reduce the passage rate of means of transport, for being the commander control of target to transport mechanized infantry's minimum that expends time in, this reduction has been equivalent to increase the length of transportation route, transportation route length after claiming to increase is equivalent path length, the without hindrance transportation probability of transportation route is with the function of time as variable, equivalent transportation route length then is with the function of the without hindrance transportation probability of actual shipment path and relevant transportation route as variable, when the without hindrance transportation probability of transportation route is 1, actual shipment path and equivalent transportation route equal in length.

5, the quick commander's control method of disposing of battlefield mechanized infantry according to claim 1, it is characterized in that described structure is that the target of commander's controlling models of target objective function of being meant this commander's controlling models is transported all infantries minimum that expends time in for making to transport all infantries minimum that expends time in, but when the without hindrance transportation probability of the transportation route in all paths was 1, the target of the objective function of this commander's controlling models was simultaneously also for making the carrying capacity of transporting all infantries' needs for minimum.

6, commander's control method that battlefield mechanized infantry according to claim 1 disposes fast, it is characterized in that described and use linear programming, the dual program method of linear programming is found the solution this model, by two-dimentional form solving result is updated again, meeting option control command that quick deployment time requires until final acquisition is meant by the method for finding the solution linear programming and finding the solution the dual program of linear programming and finds the solution commander's controlling models, can obtain minimum time respectively from different assembly place Transport Machinery infantries to different deployment points needs, with different assembly places and the relevant shadow price of different deployment points constraint condition, the result that will find the solution inserts in a kind of two dimension commander's control form again, according to analysis to this two dimension commander control form, and pass through according to shadow price, the time bottleneck is adjusted correlation parameter, constantly find the solution and update, meet the option control command that the battlefield mechanized infantry requires quick deployment time until final acquisition.

7, commander's control method that battlefield mechanized infantry according to claim 1 disposes fast, it is characterized in that described and use linear programming, the dual program method of linear programming is found the solution this model, by two-dimentional form solving result is updated again, meeting until final acquisition that option control command that quick deployment time requires is meant can be by describing from each assembly place as the zones of different in the two-dimentional form of option control command to each deployment point Transport Machinery infantry's quantity, each deployment point needs the size of transport power, the quantity of means of transport, the minimum time that transportation expends can be disposed mechanized infantry's quantity with relevant shadow price, each assembly place, the situation of change of residue mechanized infantry quantity is with relevant shadow price and transport the minimum time that all mechanized infantries expend.

8, commander's control method that battlefield mechanized infantry according to claim 1 disposes fast, it is characterized in that the length of described this method according to mechanized infantry's transportation route from different assembly places to different deployment points, the without hindrance transportation probability of transportation route, the assembly place infantry can the deployment amount and the deployment point to infantry's demand, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all infantries minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution the case study that this model is meant that the following quick commander that the battlefield mechanized infantry is disposed fast controls, but following mathematical formulae, derivation, result of calculation and application process are applicable to commander's control that all battlefield mechanized infantries are disposed fast

Supposing that the quick deployment issue of battlefield mechanized infantry can be used by m supply mechanized infantry's assembly place and n demand mechanized infantry's deployment point and between different supply and demand nodes exists the network in a Transport Machinery infantry's path to describe, and is x from supplying mechanized infantry's quantity that node i transports to demand node j _Ij, the without hindrance transportation probability of transportation route is p _Ij(t), the physical length of transportation route is r _Ij, the equivalent length of transportation route is d _IjThe without hindrance transportation probability of transportation route is meant that complicated battlefield surroundings may impact the traffic capacity of mechanized infantry's transportation route, thereby reduce the passage rate of means of transport, for being the commander control of target to transport mechanized infantry's minimum that expends time in, this reduction has been equivalent to increase the length of transportation route, transportation route length after claiming to increase is equivalent path length, the without hindrance transportation probability of transportation route is with the function of time as variable, equivalent transportation route length then is with the function of the without hindrance transportation probability of actual shipment path and relevant transportation route as variable, when the without hindrance transportation probability of transportation route is 1, actual shipment path and equivalent transportation route equal in length

The problem that need to solve is that one of design is transported the mechanized infantry to n deployment point from m assembly place, make the carrying capacity and the consumed time of transporting all mechanized infantry's costs be minimum movement plan simultaneously, and calculate the quantity that the required means of transport of mechanized infantry is transported in each assembly place, it is as follows that relevant mechanized infantry disposes commander controlling models and linear programming equation:

Objective function: $\min Z=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{d}_{\mathrm{ij}}{x}_{\mathrm{ij}}$

The deployment point demand equals constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{ie}}=D_e,(e=1,\·\·\·,n_e)$

The deployment point demand is less than constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{il}}\≤D_l,(l=n_e+1,\·\·\·,n_l)$

The deployment point demand is greater than constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{is}}\≥D_s,(s=n_l+1,\·\·\·,n_s)$

The assembly place supply equals constraint condition: $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ej}}=S_e,(e=n_s+1,\·\·\·,m_e)$

The assembly place supply is less than constraint condition: $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{lj}}\≤S_l,(l=m_e+1,\·\·\·,m_l)$

The assembly place is in large supply in constraint condition: $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{sj}}\≥S_s,(s=m_l+1,\·\·\·,m_s)$

Condition of Non-Negative Constrains: x _Ij〉=0, (i=1 ..., m; J=1 ..., n)

The classification of the amount relevant with the deployment point Demand Constraint: $D_v=\left\{\begin{array}{c}{D}_e,(1\≤v\≤n_e)\\ D_l,(n_e+1\≤v\≤n_l)\\ D_s,(n_l+1\≤v\≤n_s)\end{array}\right.$

The classification of the amount relevant with assembly place supply constraint: $S_u=\left\{\begin{array}{c}{S}_e,(n_s+1\≤u\≤m_e)\\ S_l,(m_e+1\≤u\≤m_l)\\ S_s,(m_l+1\≤u\≤m_s)\end{array}\right.$

The equivalent length of transportation route is: d _Ij=f (r _Ij, p _Ij(t)), (0＜p _Ij(t)≤1; I=1 ..., m; J=1 ..., n)

Assembly place i (i=1 ... m) the means of transport quantity of Xu Yaoing

From assembly place i (i=1 ... m) transport the mechanized infantry to deployment point j (j=1 ... n) spent time: $T_{\mathrm{ij}}=\frac{d_{\mathrm{ij}}}{C}$

Finish all mechanized infantries and dispose spent minimum time: minT=max{T _Ij}

Wherein:

M is supply mechanized infantry's assembly place sum;

N is demand mechanized infantry's a deployment point sum;

r _IjFor assembly place i (i=1 ... m) with deployment point j (j=1 ... the physical length of the transportation route n) (unit: kilometer);

p _Ij(t) be assembly place i (i=1 ... m) with deployment point j (j=1 ... n) the without hindrance transportation probability of the transportation route between is with the function of time t as variable;

d _IjFor assembly place i (i=1 ... m) with deployment point j (j=1 ... the equivalent length of the transportation route n) (unit: kilometer), when

p _Ij(t)=1 o'clock, r _IjWith d _IjEquate;

E is the sequence number that equals the amount of equaling of constraint condition;

L is the sequence number less than the constraint condition upper limit;

S is the sequence number greater than the constraint condition lower limit;

n _eMaximum sequence number for the equal amount that equal constraint condition relevant with the deployment point demand;

n _lBe the maximum sequence number less than the constraint condition upper limit relevant with the deployment point demand;

n _sBe the maximum sequence number greater than constraint condition lower limit relevant with the deployment point demand;

D _eFor with the deployment point need the relevant amount of mechanized infantry's quantity (e=1 ..., n _e) (unit: the people);

D _lFor needing the relevant upper limit (l=n of mechanized infantry's quantity with the deployment point _e+ 1 ..., n _l) (unit: the people);

D _sFor needing the relevant lower limit (s=n of mechanized infantry's quantity with the deployment point _l+ 1 ..., n _s) (unit: the people);

m _eMaximum sequence number for the equal amount that equal constraint condition relevant with the assembly place supply;

m _lBe the maximum sequence number less than the constraint condition upper limit relevant with the assembly place supply;

m _sBe the maximum sequence number greater than constraint condition lower limit relevant with the assembly place supply;

S _eFor supplying mechanized infantry's the relevant amount (e=n of quantity with the assembly place _s+ 1 ..., m _e) (unit: the people);

S _lFor supplying mechanized infantry's quantity the relevant upper limit (l=m with the assembly place _e+ 1 ..., m _l) (unit: the people);

S _sFor supplying mechanized infantry's quantity relevant lower limit (s=m with the assembly place _l+ 1 ..., m _s) (unit: the people);

V _iFor the supply mechanized infantry assembly place i (i=1 ... m) transport the means of transport quantity that the mechanized infantry needs;

L transports mechanized infantry's ability (unit: the people) for each means of transport;

C transports mechanized infantry's speed (unit: kilometer/hour) for each means of transport;

Above-mentioned model shows: try to achieve by linear programming on the basis of minZ value, can calculate mechanized infantry's quantity x that each assembly place must be transported to the related deployment point _Ij,, can calculate the means of transport quantity V that each assembly place needs again according to the dead weight capacity L of means of transport _iTransport mechanized infantry's speed C and the longest path between assembly place and deployment point at last according to means of transport, can calculate again and finish the spent shortest time T of whole mechanized infantry's deployment task, thereby realize that the commander that the battlefield mechanized infantry is disposed fast controls, for constraint condition rationally being set, improving solvability, utilizing above-mentioned linear programming model better, the dual linear programming model that provides this model is as follows:

Objective function: $\max G=\underset{v=1}{\overset{n_e}{\mathrm{\Σ}}}{D}_v{y}_v+\underset{v=n_e+1}{\overset{n_l}{\mathrm{\Σ}}}{D}_v{y}_v+\underset{v=n_l+1}{\overset{n_s}{\mathrm{\Σ}}}{D}_v{y}_v+\underset{u=n_s+1}{\overset{m_e}{\mathrm{\Σ}}}{S}_u{y}_u+\underset{u=m_e+1}{\overset{m_l}{\mathrm{\Σ}}}{S}_u{y}_u+\underset{u=m_l+1}{\overset{m_s}{\mathrm{\Σ}}}{S}_u{y}_u$

Constraint condition: $D_e{y}_{n_e\left(j\right)}+D_l{y}_{n_l\left(j\right)}+D_s{y}_{n_s\left(j\right)}+S_e{y}_{m_e\left(i\right)}+S_l{y}_{m_l\left(i\right)}+S_s{y}_{m_s\left(i\right)}\≤d_{\mathrm{ij}}(i=1,\·\·\·,m;j=1,\·\·\·,n)$

Condition of Non-Negative Constrains: $y_{m_l\left(i\right)},y_{n_l\left(j\right)}\≤0(i=1,\·\·\·,m;j=1,\·\·\·,n)$

Non-positive constraint condition: $y_{m_s\left(i\right)},y_{n_s\left(j\right)}\≥0(i=1,\·\·\·,m;j=1,\·\·\·,n)$

Wherein: $y_{n_e\left(j\right)}=y_v(1\≤v\≤n_e),$ $y_{n_l\left(j\right)}=y_v(n_e+1\≤v\≤n_l),$ $y_{n_s\left(j\right)}=y_v(n_l+1\≤v\≤n_s)$ Be the variable subscript sequence number transforming function transformation function relevant with j; $y_{m_e\left(i\right)}=y_u(n_s+1\≤u\≤m_e),$ $y_{m_l\left(i\right)}=y_u(m_e+1\≤u\≤m_l),$ $y_{m_s\left(i\right)}=y_u(m_l+1\≤u\≤m_s)$ Be the variable subscript sequence number transforming function transformation function relevant with i;

y _v, y _u(v=1 ..., n _sU=n _s+ 1 ..., m _s) be respectively the relevant decision variable of shadow price with the demand of former linear programming and supply mechanized infantry constraint condition;

Since primal linear programming solves be with deployment point j and assembly place i (i=1 ..., m; J=1 ..., the resource optimal utilization problem that constraint condition n) is relevant, thus dual program solve then be estimate to make deployment point j and assembly place i (i=1 ..., m; J=1 ..., constraint condition n) satisfies the cost problem that must pay, promptly uses the valency problem, and shadow price y _vAnd y _uReflection make just deployment point j and assembly place i (i=1 ..., m; J=1, n) constraint condition satisfies the cost that must pay, by making the target function value relevant minimize (or maximization) with cost, shadow price can be used for each constraint condition of comparison and carry out equivalence analysis to the contribution of target function value or to this contribution influence, the implication of a certain constraint condition shadow price is when the constant of its pairing constraint condition right-hand member increases a unit, the numerical value that former problem objective function optimal value increases, shadow price is big more, show that this constraint condition is big more to the influence of the minimum delivery power of option control command, the difficulty that satisfies this condition is big more, therefore, by comparing shadow price and realistic objective functional value, can the variation that can study former linear programming constraint condition make objective function obtain gain.

9, commander's control method that battlefield mechanized infantry according to claim 1 disposes fast, it is characterized in that the length of described this method according to mechanized infantry's transportation route from different assembly places to different deployment points, the without hindrance transportation probability of transportation route, the assembly place infantry can the deployment amount and the deployment point to infantry's demand, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all infantries minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model, by two-dimentional form solving result is updated again, the option control command that meets quick deployment time requirement until final acquisition is meant if the option control command of trying to achieve can not satisfy the preset time requirement, then can be by two dimension commander control table, result to former linear programming and dual program analyzes, determine to influence the bottleneck that the battlefield mechanized infantry disposes T.T., carry out reasonable disposition by mechanized infantry's quantity again to the assembly place, increase the quantity of means of transport and adopt different means such as means of transport, eliminate the time bottleneck, and repeat this process, until the predetermined requirement that meets T.T. that makes battlefield mechanized infantry deployment, this process can be described with following example, but the mathematical formulae described in example, result of calculation, various forms and application process are applicable to commander's control that all battlefield mechanized infantries are disposed fast

Suppose that certain mechanization combat division must be that 16 people, average speed per hour are 70 kilometers armored personnel carrier with dead weight capacity, transport the mechanized infantry of specified amount to 14 deployment points from 6 assembly places, between assembly place and the deployment point transportation route length, assembly place infantry can the deployment amount and the deployment point as shown in table 1 to the bound of infantry's demand, make the without hindrance transportation Probability p of all transportation routes here _Ij(t) be 1, d _Ij=r _Ij/ p _Ij(t), therefore actual shipment path and equivalent transportation route equal in length, the i.e. r between different supply and demand sides _IjWith d _IjEquate,

Table 1: transportation route length and portion's amount of asking between mechanization combat division assembly place and the deployment point (unit: axiom, people) 01 assembly place 02 assembly place 03 assembly place 04 assembly place 05 assembly place 06 assembly place The demand upper limit The demand lower limit 14 deployment points, 13 deployment points, 12 deployment points, 11 deployment points, 10 deployment points, 09 deployment point, 08 deployment point, 07 deployment point, 06 deployment point, 05 deployment point, 04 deployment point, 03 deployment point, 02 deployment point, 01 deployment point 37.00 34.00 25.00 14.00 26.00 24.00 120.00 159.00 112.00 62.00 91.00 126.00 90.00 81.00 13.00 25.00 28.00 15.00 85.00 20.00 98.00 138.00 96.00 37.00 66.00 97.00 58.00 56.00 70.00 83.00 108.00 97.00 82.00 110.00 12.00 51.00 96.00 46.00 17.00 81.00 99.00 20.00 74.00 87.00 112.00 101.00 86.00 100.00 129.00 149.00 25.00 50.00 79.00 86.00 104.00 66.00 44.00 31.00 66.00 58.00 56.00 39.00 105.00 145.00 110.00 59.00 73.00 27.00 11.00 75.00 60.00 19.00 56.00 30.00 48.00 65.00 75.00 30.00 69.00 70.00 26.00 65.00 72.00 44.00 36.00 21.00 90.00 130.00 70.00 40.00 60.00 16.00 29.00 36.00 90.00 30.00 35.00 28.00 36.00 21.00 90.00 130.00 70.00 40.00 60.00 16.00 29.00 36.00 80.00 20.00 25.00 22.00 Can keep supplying limit 100.00 200.00 300.00 400.00 150.00 350.00 Can supply lower limit 100.00 60.00 40.00 10.00 10.00 20.00

According to above-mentioned linear programming and commander controlling models and relevant dual linear programming model, the option control command that the minimum time mechanized infantry of mechanization combat division who calculates by simplex algorithm disposes is as shown in table 2,

Table 2: mechanization combat division minimum time is disposed option control command (unit: people, passenger-kilometer,, minute) 01 assembly place 02 assembly place 03 assembly place 04 assembly place 05 assembly place 06 assembly place Ton kilometre The truck number Need the time Upper limit shadow valency Lower limit shadow valency 14 deployment points, 13 deployment points, 12 deployment points, 11 deployment points, 10 deployment points, 09 deployment point, 08 deployment point, 07 deployment point, 06 deployment point, 05 deployment point, 04 deployment point, 03 deployment point, 02 deployment point, 01 deployment point 30.00 70.00 36.00 60.00 64.00 40.00 60.00 36.00 80.00 22.00 29.00 20.00 25.00 21.00 66.00 16.00 468.00 399.00 2430.00 2940.00 1820.00 800.00 720.00 480.00 725.00 1656.00 1360.00 540.00 275.00 440.00 3 2 6 9 5 3 4 1 2 3 5 2 2 2 11.14 16.29 24.00 25.71 22.29 17.14 10.29 25.71 21.43 39.43 14.57 23.14 9.43 17.14 13.00 19.00 25.00 14.00 26.00 20.00 12.00 30.00 25.00 37.00 0.00 0.00 0.00 0.00 13.00 19.00 25.00 14.00 26.00 20.00 12.00 30.00 25.00 37.00 17.00 27.00 11.00 20.00 Add up to 100.00 200.00 198.00 29.00 45.00 103.00 15053.00 49 39.43 ^* Quantity available 100.00 200.00 300.00 400.00 15.000 350.00 For the back surplus 0.00 0.00 102.00 371.00 105.00 247.00 Upper limit shadow valency 0.00 0.00 0.00 0.00 0.00 0.00 Lower limit shadow valency 0.00 0.00 0.00 0.00 0.00 0.00

* finish the minimum time that deployment task needs

By option control command (table 2) is analyzed as can be known; the armored personnel carrier that finishing deployment task needs adds up to 49; time is 39.43 minutes; the armored personnel carrier that 01～06 assembly place needs is respectively 11; 16; 14; 2; 4 and 12; therefore must be to 02; 03 and 06 assembly place implements to lay special stress on protecting; further analyze as can be known; transporting 36 39.43 minutes that the mechanized infantry spent from 03 assembly place to 10 deployment points is bottlenecks that the whole deployment task of restriction is finished sooner; if finish this part mechanized infantry's transportation with helicopter; then can be shortened to 25.71 minutes the time of finishing whole deployment task; reduction is 34.80%

From to demand constraint condition D _v(v=1,18) analysis of shadow price as can be known, the size of price has truly reflected the complexity that the related constraint condition satisfies, shadow price is 0 to be meant in specific span, relevant constraint condition does not constitute influence to target function value, the easiest to be satisfied, promptly this resource is not in short supply, if increase this resource again the optimal value of objective function is further reduced, again for example, in order to satisfy constraint condition D ₁₀, transported the mechanized infantry 39.43 minutes consuming time to 10 deployment points, the shadow price of this constraint condition is a maximal value 37, illustrates that this condition is the most difficult satisfied, can be by D with similar method _vThe complexity that satisfies, from difficulty to easy ordering: D ₁₀, D ₈, D ₁₆, D ₅, D ₃, D ₉..., to supply constraint condition S _u(u=19 ..., 29) analysis of shadow price as can be known, their shadow price is 0, therefore, in specific span, changes S _uValue target function value is not constituted influence, must be pointed out that shadow price is not changeless, can be along with D _vAnd S _uVariation and change, make the resource that does not constitute influence originally become influential resource, by analysis to shadow price, can adjust constraint condition targetedly, reach the purpose that reduces carrying capacity and haulage time, because shadow price is the result who obtains, only in its valid interval under specific constraint condition, price just has relative stability

Measure as can be seen from the residue mechanized infantry of each assembly place, back of finishing the work, the mechanized infantry of 02 assembly place exhausts, obviously on the low side, and that the mechanized infantry of 04 assembly place measures is obviously bigger than normal, and according to the antithesis analysis, the shadow price of their constraint condition is 0, this statement of facts: if there is more mechanized infantry 02 assembly place, there is mechanized infantry still less 04 assembly place, just may obtain better to map out the plan, so adjust the upper limit S of constraint condition targetedly ₂₅Be increased to 400 from 200, make S simultaneously ₂₇Reduce to 200 from 400, the improvement project that the mechanization combat division minimum time of obtaining is disposed is as shown in table 3,

Table 3: mechanization combat division minimum time is disposed the improvement project (unit: people, passenger-kilometer,, minute) of commander's control 01 assembly place 02 assembly place 03 assembly place 04 assembly place 05 assembly place 06 assembly place Ton kilometre The truck number Need the time Upper limit shadow valency Lower limit shadow valency 14 deployment points, 13 deployment points, 12 deployment points, 11 deployment points, 10 deployment points, 09 deployment point, 08 deployment point, 07 deployment point, 06 deployment point, 05 deployment point, 04 deployment point, 03 deployment point, 02 deployment point, 01 deployment point 30.00 70.00 36.00 60.00 130.00 40.00 36.00 60.00 80.00 22 29.00 20.00 25.00 21.00 16.00 468.00 399.00 2430.00 1950.00 1820.00 800.00 720.00 480.00 725.00 1332.00 1360.00 54.000 275.00 440.00 3 2 6 9 5 3 4 1 2 3 5 2 2 2 11.14 16.29 24.00 12.86 22.29 17.14 10.29 25.71 21.43 31.71 14.57 23.14 9.43 17.14 13.00 19.00 25.00 14.00 26.00 20.00 12.00 30.00 25.00 37.00 0.00 0.00 0.00 0.00 13.00 19.00 25.00 14.00 26.00 20.00 12.00 30.00 25.00 37.00 17.00 27.00 11.00 20.00 Add up to 100.00 302.00 162.00 29.00 45.00 37.00 13739.00 49 31.71 ^* Quantity available 100.00 400.00 300.00 200.00 150.00 350.00 For the back surplus 0.00 98.00 138.00 171.00 105.00 313.00 Upper limit shadow valency 0.00 0.00 0.00 0.00 0.00 0.00 Lower limit shadow valency 0.00 0.00 0.00 0.00 0.00 0.00

* finish the minimum time that deployment task needs

Analysis by his-and-hers watches 3 as can be known, the time that finishing deployment task needs shortens to 31.71 minutes, amount of decrease is 19.58%, total carrying capacity is reduced to 13739 passenger-kilometers, and amount of decrease is 8.73%, and antithesis the analysis showed that: shadow price is without any variation, but the scheme after improving is better, therefore, can also carry out reasonable configuration to the mechanized infantry of each assembly place with said method, realization can be disposed the Optimal Management of mechanized infantry's quantity.