CN1845148A - Command control method of rapid transport for war field wounded person - Google Patents

Abstract

The invention relates to a quick command control method for quickly transporting wounded person in low risk. Wherein, the commanded object the all wounded persons; according to the lengths from different receivers to different senders, the transmission non-baffle probability, the receiving amount of receiver, the sent amount of sender, and the load and speed of transmission device, the command control mode purposed for transporting all wounded persons 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 low-risk transporting. The invention can improve the battle effectiveness, with wider application. The invention also provides relative technique.

Description

Commander's control method of a kind of battlefield wounded's rapid transport

Technical field the present invention relates to national defence and association area, is used for battlefield wounded's rapid transport is implemented commander's control, realizes the rapid transport to the battlefield wounded.

Background technology is implemented quick wounded's transhipment between the take over party in battlefield and the side of transporting commander's control is an important component part of operational commanding control, the wounded described here comprise the patient, the length of transporting the path to the different side of the transporting wounded according to different take over partys, the without hindrance transportation probability of transportation route, the take over party wounded's the quantities received and the side of the transporting wounded's upwards of movement, the speed of means of transport and carrying capacity, working out one is that to be the battlefield commander implement the key issue that commander's control must solution to battlefield wounded's rapid transport for the transhipment commander control plan of target to realize that the take over party and the side of transporting transport all wounded minimum that expends time in, the solution of this problem is for increasing substantially fighting capacity, the demand of instrument is transported in minimizing to the battlefield wounded, guarantee that the wounded are in time given treatment to, have crucial meaning.

Wounded's rapid transport ability is most important for the triumph of capturing IT-based warfare, complicated battlefield surroundings may impact the traffic capacity that the wounded transport the path, thereby reduce the passage rate of means of transport, and commander's control of wounded's transhipment is the key that improves mobile operations fast, and wherein the matter of utmost importance that must solve is commander's control plan of wounded's transhipment of formulation science.Can the quality of this plan not only be related to and implements the battlefield wounded and transport what of institute's consumption of natural resource, in time obtain treatment but also be related to some severely injured peoples, descends to guarantee fighting capacity to be unlikely to the delay that member due to wound transports.

Time seems more important for commander's control of battlefield wounded transhipment and this transhipment, therefore must analyze the choose reasonable parameter by antithesis and improve solvability and come the control to battlefield wounded's rapid transport enforcement commander with transhipment time minimum as optimization aim.

The present invention relates to commander's control method of battlefield wounded's rapid transport, relate to military affairs and association area, the object of commander's control is all battlefield wounded, this method is according to the length of transporting the path to the difference side of the transporting wounded from different take over partys, the without hindrance transportation probability of transportation route, the take over party wounded's the quantities received and the side of the transporting wounded's upwards of movement, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all wounded 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 battlefield wounded's rapid transport time requirement 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 of all battlefield wounded's rapid transports, the invention further relates to the technology that realizes this method.

Summary of the invention the present invention is according to the length of transporting the path to the difference side of the transporting wounded from different take over partys, the without hindrance transportation probability of transportation route, the take over party wounded's the quantities received and the side of the transporting wounded's upwards of movement, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all wounded minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model, obtain scheme to battlefield wounded's rapid transport enforcement commander control with two-dimentional form description, and check whether this option control command meets and finish the time requirement that the whole battlefield wounded transport task, if do not meet the demands, then by analysis to this two dimension commander control form, and according to shadow price, wounded's quantities received that the time bottleneck allows correlation reception side and means of transport etc. are adjusted, constantly repeat this and find the solution-check analytic process, meet the option control command of battlefield wounded's rapid transport time requirement until final acquisition.Therefore, the conception of commander's control of battlefield wounded's rapid transport is 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, come this model of rapid solving by reducing constraint condition, obtain scheme to battlefield wounded's rapid transport enforcement commander control with two-dimentional form description, and according to the time requirement of finishing whole wounded's transhipment, finish the time bottleneck that the whole battlefield wounded transport task by searching influence, the take over party allows to receive the unreasonable configuration of wounded's amount and means of transport is adjusted, continue to optimize and improve this option control command, and the final time requirement that obtains to satisfy battlefield wounded's rapid transport, option control command with two-dimentional form description becomes key character of the present invention.

The technical scheme of commander's control method of a kind of battlefield of the present invention wounded's rapid transport is:

At first, battlefield wounded's rapid transport problem definition is the supply and demand system that the side of transporting constituted by the wounded's the take over party and the wounded, the feature of this system can be with the length of transporting the path to the difference side of the transporting wounded from different take over partys, the without hindrance transportation probability of transportation route, the take over party wounded's the quantities received and the side of the transporting wounded's upwards of movement, the speed and the carrying capacity of means of transport are described, and according to the time requirement that the battlefield wounded are transported, structure is commander's controlling models of target to transport all wounded minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model, obtain scheme to battlefield wounded's rapid transport enforcement commander control with two-dimentional form description, time bottleneck by continuous searching supply and demand system, the quantity that relevant take over party allows to receive the wounded is carried out reasonable disposition, adopt methods such as different means of transports, the final time requirement that obtains to satisfy battlefield wounded's rapid transport, the battlefield wounded are transported the scheme of implementing commander's control, finish commander's control battlefield wounded's rapid transport.

Complicated battlefield surroundings may impact the traffic capacity of wounded's transportation route, thereby reduce the passage rate of means of transport, for being the commander control of target to transport wounded'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 transported all wounded minimum that expends time in for making, 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 wounded's needs for 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 receive the minimum time that needs from the difference side of the transporting wounded from different take over partys, with different take over partys and the relevant shadow price of the different sides of transporting constraint condition, 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 of battlefield wounded's rapid transport time requirement.

Can describe from each side of transporting to each take over party by the zones of different in the two dimension commander control form and transport the wounded's quantity, the size that each side of transporting needs transport power, the quantity of means of transport, the minimum time and relevant shadow price that transportation expends, the situation of change of quantity, residue permission reception wounded quantity that each take over party receives the wounded is with relevant shadow price and transport the minimum time that all wounded 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 wounded transport T.T., carry out reasonable disposition, increase the quantity of means of transport and adopt different means such as means of transport by the take over party being allowed receive wounded's quantity again, eliminate the time bottleneck, and repeat this process, until making the predetermined requirement that meets T.T. of finishing battlefield wounded transhipment.

Commander's control method of battlefield wounded's rapid transport of the present invention's design is applicable to that all battlefield wounded's rapid transports are key characters of the present invention.

The case study of commander's control of battlefield wounded's rapid transport is as follows.

Suppose that the battlefield wounded's transportation problem can transport wounded's node and describe in different receptions and the network that transports the path that has transportation wounded between the node with receiving wounded's node and n by m, receive from receiving node i that to transport wounded's quantity that node j transports be x _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 wounded's transportation route, thereby reduce the passage rate of means of transport, for being the commander control of target to transport wounded'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 receives node from m and receives the individual wounded that transport node from n, make the carrying capacity and the consumed time of transporting all wounded's costs be minimum diversion plan simultaneously, and calculate each and transport the quantity that node transports the required means of transport of the wounded, it is as follows that the relevant battlefield wounded transport commander controlling models and linear programming equation:

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

Upwards of movement equals constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{ie}}=D_e,$ (e＝1，…，n _e)

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

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

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

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

Quantities received is greater than 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 transporting 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 receiving 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)

Arrival reception node i (i=1 ... m) means of transport quantity V _i:

Reception node i (i=1 ... m) receive from transport node j (j=1 ... n) time that the wounded are spent: $T_{\mathrm{ij}}=\frac{d_{\mathrm{ij}}}{C}$

Finish all battlefield wounded and transport spent minimum time: minT=max{T _Ij}

Wherein:

M is for receiving the wounded's node sum;

N is the node sum that transports the wounded;

r _IjFor receive node i (i=1 ... m) with transport node j (j=1 ... the physical length of the transportation route n) (unit: kilometer);

p _Ij(t) for receive node i (i=1 ... m) with transport node 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 receive node i (i=1 ... m) with transport node 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 transporting the node upwards of movement;

n _lBe the maximum sequence number less than the constraint condition upper limit relevant with transporting the node upwards of movement;

n _sBe the maximum sequence number greater than constraint condition lower limit relevant with transporting the node upwards of movement;

D _eFor with transport node transport the relevant amount of the wounded's quantity (e=1 ..., n _e) (unit: the people);

D _lFor with transport node and transport the relevant upper limit (l=n of wounded's quantity _e+ 1 ..., n _l) (unit: the people);

D _sFor with transport node and transport the relevant lower limit (s=n of wounded's quantity _l+ 1 ..., n _s) (unit: the people);

m _eFor allowing to receive the maximum sequence number that the wounded measure the relevant amount of equaling that equals constraint condition with the reception node;

m _lMeasure relevant maximum sequence number for allowing to receive the wounded less than the constraint condition upper limit with the reception node;

m _sMeasure relevant maximum sequence number for allowing to receive the wounded greater than the constraint condition lower limit with the reception node;

S _eFor allowing to receive the relevant amount (e=n of wounded's quantity with the reception node _s+ 1 ..., m _e) (unit: the people);

S _lFor allowing to receive the relevant upper limit (l=m of wounded's quantity with the reception node _e+ 1 ..., m _l) (unit: the people);

S _sFor allowing to receive the relevant lower limit (s=m of wounded's quantity with the reception node _l+ 1 ..., m _s) (unit: the people);

V _iFor arrive to receive wounded's node i (i=1 ... m) the means of transport quantity of transporting the wounded;

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

C transports the wounded'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 each and transport wounded's quantity x that node must transport to the correlation reception node _Ij,, can calculate and arrive the means of transport quantity V that each receives node again according to the dead weight capacity L of means of transport _iAnd the means of transport quantity of transporting the node needs, at last transport the wounded's speed C and at the longest path that receives and transport between the node according to means of transport, can calculate again and finish the whole wounded and transport the spent shortest time T of task, thereby realize commander's control to battlefield wounded's rapid transport, 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 shadow price of transporting and receive wounded's constraint condition or the relevant decision variable of opportunity cost with former linear programming;

Since primal linear programming solves be with transport node j and receive node 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 transport node j and receive node 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 _uThe making just of reflection transport node j and receive node 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, 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, but it is also just difficult more to satisfy this condition, therefore, introducing shadow price just can be by comparing shadow price and realistic objective functional value, and can variation that study former linear programming constraint condition make objective function obtain gain.

Embodiment

Implementation example

In IT-based warfare, battlefield wounded's turn-over capacity of mechanization combat division is an important component part of its fighting capacity, to battlefield wounded's turn-over capacity and the demand of time, makes commander's control of implementing battlefield wounded transhipment become vital task.Suppose that certain mechanization combat division must be that 16 people, average speed per hour are wounded's transfer car(buggy) of 70 kilometers with dead weight capacity, transport the battlefield wounded that a little transport from 6 acceptance points receptions from 14, receive and transport a little between the bound of length, quantities received and upwards of movement of transportation route as shown in table 1, make the without hindrance transportation Probability p of all transportation routes here _Ij(t) be 1, d _Ij=r _Ij/ p _Ij(t), therefore difference receive and the side of transporting between actual shipment path and equivalent transportation route equal in length, i.e. r _IjWith d _IjEquate,

Table 1: the battlefield wounded receive and transport a little between transportation route length, reception and upwards of movement (unit: kilometer, people)

	01 acceptance point	02 acceptance point	03 acceptance point	04 acceptance point	05 acceptance point	06 acceptance point	Transport the upper limit	Transport lower limit
									01 transports a little 02 transports a little 03 and transports a little 04 and transport a little 05 and transport a little 06 and transport a little 07 and transport a little 08 and transport a little 09 and transport a little 10 and transport a little 11 and transport a little 12 and transport a little 13 and transport a little and 14 transport a little	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 connect limit	100.00	200.00	300.00	400.00	150.00	350.00
									Can connect 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, it is as shown in table 2 that the minimum time wounded of mechanization combat division that calculate by simplex algorithm transport option control command,

Table 2: the minimum time wounded of mechanization combat division transport option control command (unit: people, passenger-kilometer,, minute)

	01 acceptance point	02 acceptance point	03 acceptance point	04 acceptance point	05 acceptance point	06 acceptance point	Passenger-kilometer	Fortune car number	Need the time	Upper limit shadow valency	Lower limit shadow valency
												01 transports a little 02 transports a little 03 and transports a little 04 and transport a little 05 and transport a little 06 and transport a little and 07 transport a little	30.00 70.00	36.00 60.00 64.00 40.00	60.00			21.00 66.00	468.00 399.00 2430.00 2940.00 1820.00 800.00 720.00	3 2 6 9 5 3 4	11.14 16.29 24.00 25.71 22.29 17.14 10.29	13.00 19.00 25.00 14.00 26.00 20.00 12.00	13.00 19.00 25.00 14.00 26.00 20.00 12.00

08 transports a little 09 transports a little 10 and transports a little 11 and transport a little 12 and transport a little 13 and transport a little and 14 transport a little			36.00 80.00 22.00	29.00	20.00 25.00	16.00	480.00 725.00 1656.00 1360.00 540.00 275.00 440.00	1 2 3 5 2 2 2	25.71 21.43 39.43 14.57 23.14 9.43 17.14	30.00 25.00 37.00 0.00 0.00 0.00 0.00	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 *
Can connect quantity	100.00	200.00	300.00	400.00	150.00	350.00
												Connect 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

* finishing the minimum time that the transhipment task expends is 39.43 minutes

By option control command (table 2) is analyzed as can be known; wounded's transfer car(buggy) that finishing the transhipment task needs adds up to 49; time is 39.43 minutes; wounded's transfer car(buggy) that 01～06 acceptance point receives is respectively 11; 16; 14; 2; 4 and 12; therefore must be to 02; 03 and 06 acceptance point is implemented to lay special stress on protecting; further analyze as can be known; transporting 36 39.43 minutes that the wounded spent of a little transporting from the reception of 03 acceptance point from 10 is the bottleneck that the whole transhipment task of restriction is finished sooner; if finish this part wounded's transhipment with helicopter; then can be shortened to 25.71 minutes the time that whole transport task is finished; reduction is 34.80%

From to upwards of movement 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, 10 transport and a little transported the wounded 39.43 minutes consuming time, and the shadow price of this constraint condition is a maximal value 37, illustrates that this condition is the most difficult to satisfy, 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 quantities received 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 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.

In addition, from finish the work the back each acceptance point the residue quantities received as can be seen, the permission quantities received of 02 acceptance point exhausts, obviously on the low side, and the permission quantities received of 04 acceptance point 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 02 acceptance point has more permission quantities received, 04 acceptance point has permission still less

Quantities received just may obtain better diversion 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 of the minimum time transhipment of obtaining is as shown in table 3,

Table 3: the improvement project (unit: people, passenger-kilometer,, minute) of mechanization combat division minimum time transhipment

	01 acceptance point	02 acceptance point	03 acceptance point	04 acceptance point	05 acceptance point	06 acceptance point	Passenger-kilometer	Fortune car number	Need the time	Upper limit shadow valency	Lower limit shadow valency
												01 transports a little 02 transports a little 03 and transports a little 04 and transport a little 05 and transport a little 06 and transport a little 07 and transport a little 08 and transport a little 09 and transport a little 10 and transport a little 11 and transport a little 12 and transport a little 13 and transport a little and 14 transport a little	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	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 *
												Can connect quantity	100.00	400.00	300.00	200.00	150.00	350.00
Connect 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 the transhipment task needs

Analysis by his-and-hers watches 3 as can be known, the time that finishing the transhipment 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 allow the wounded that receive to carry out reasonable configuration to each acceptance point, realize allowing the Optimal Management of quantities received with said method.

Claims (9)

1, the present invention relates to commander's control method of battlefield wounded's rapid transport, relate to military affairs and association area, the object of commander's control is all battlefield wounded, this method is according to the length from different take over partys to the difference side of transporting wounded transportation route, the without hindrance transportation probability of transportation route, the take over party wounded's the quantities received and the side of the transporting wounded's upwards of movement, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all wounded 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 of battlefield wounded's rapid transport time requirement until final acquisition, this scheme is applicable to commander's control of all battlefield wounded's rapid transports.

2, commander's control method of battlefield according to claim 1 wounded's rapid transport, the object that it is characterized in that described commander control is meant the object as commander's control with all battlefield wounded and patient for all battlefield wounded, described commander's control is meant according to the actual demand of battlefield to wounded's transhipment, design is transported to different take over partys with the battlefield wounded from the different sides of transporting, and make total haulage time of needing or total movement capacity for minimum, can be for the scheme of implementing.

3, commander's control method of battlefield according to claim 1 wounded's rapid transport, it is characterized in that described this method is meant the supply and demand system that can set up a battlefield wounded transhipment by these parameters according to the without hindrance transportation probability of length, transportation route from different take over partys to the difference side of transporting wounded transportation route, the take over party wounded's quantities received and the side of the transporting wounded's upwards of movement, the speed and the carrying capacity of means of transport, obtains the battlefield wounded are transported the method for implementing commander's control on this basis.

4, commander's control method of battlefield according to claim 1 wounded's rapid transport, 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 wounded's transportation route, thereby reduce the passage rate of means of transport, for being the commander control of target to transport wounded'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, commander's control method of battlefield according to claim 1 wounded's rapid transport, 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 wounded minimum that expends time in for making to transport all wounded 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 wounded's needs for minimum.

6, commander's control method of battlefield according to claim 1 wounded's rapid transport, 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, the option control command that meets battlefield wounded's rapid transport time requirement until final acquisition is meant by the method for finding the solution linear programming and finding the solution the dual program of linear programming finds the solution commander's controlling models, can obtain minimum time respectively from the difference side of the transporting transportation wounded to different take over partys' needs, with different take over partys and the relevant shadow price of the different sides of transporting 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 of battlefield wounded's rapid transport time requirement until final acquisition.

7, commander's control method of battlefield according to claim 1 wounded's rapid transport, 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, the option control command that meets battlefield wounded's rapid transport time requirement until final acquisition is meant can be by describing the quantity of transporting the wounded to each take over party from each side of transporting as the zones of different in the two-dimentional form of option control command, each side of transporting needs the size of transport power, the quantity of means of transport, the minimum time that transportation expends receives the wounded's quantity with relevant shadow price, each take over party, the situation of change of residue reception wounded ability is with relevant shadow price and transport the minimum time that all wounded expend.

8, commander's control method of battlefield according to claim 1 wounded's rapid transport, it is characterized in that described this method is according to the length from different take over partys to the difference side of transporting wounded transportation route, the without hindrance transportation probability of transportation route, the take over party wounded's the quantities received and the side of the transporting wounded's upwards of movement, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all wounded minimum that expends time in, and use linear programming, the dual program method of linear programming is found the solution this model and is meant the following case study that the commander of battlefield wounded's rapid transport is controlled, but following mathematical formulae, derivation, result of calculation and application process are applicable to the commander's control to all battlefield wounded's rapid transports

Suppose that the battlefield wounded's transportation problem can transport wounded's node and describe in different receptions and the network that transports the path that has transportation wounded between the node with receiving wounded's node and n by m, receive from receiving node i that to transport wounded's quantity that node j transports be x _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 wounded's transportation route, thereby reduce the passage rate of means of transport, for being the commander control of target to transport wounded'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 receives node from m and receives the individual wounded that transport node from n, make the carrying capacity and the consumed time of transporting all wounded's costs be minimum diversion plan simultaneously, and calculate each and transport the quantity that node transports the required means of transport of the wounded, it is as follows that the relevant battlefield wounded transport commander controlling models and linear programming equation:

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

Upwards of movement equals constraint condition: $\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{x}_{\mathrm{ie}}=D_e,(e=1,\·\·\·,n_e)$

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

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

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

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

Quantities received is greater than 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 transporting 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 receiving 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)

Arrival reception node i (i=1 ... m) means of transport quantity

Reception node i (i=1 ... m) receive from transport node j (j=1 ... n) time that the wounded are spent: $T_{\mathrm{ij}}=\frac{d_{\mathrm{ij}}}{C}$

Finish all battlefield wounded and transport spent minimum time: minT=max{T _Ij}

Wherein:

M is for receiving the wounded's node sum;

N is the node sum that transports the wounded;

r _IjFor receive node i (i=1 ... m) with transport node j (j=1 ... the physical length of the transportation route n) (unit: kilometer);

p _Ij(t) for receive node i (i=1 ... m) with transport node 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 receive node i (i=1 ... m) with transport node 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 transporting the node upwards of movement;

n _lBe the maximum sequence number less than the constraint condition upper limit relevant with transporting the node upwards of movement;

n _sBe the maximum sequence number greater than constraint condition lower limit relevant with transporting the node upwards of movement;

D _eFor with transport node transport the relevant amount of the wounded's quantity (e=1 ..., n _e) (unit: the people);

D _lFor with transport node and transport the relevant upper limit (l=n of wounded's quantity _e+ 1 ..., n _l) (unit: the people);

D _sFor with transport node and transport the relevant lower limit (s=n of wounded's quantity _l+ 1 ..., n _s) (unit: the people);

m _eFor allowing to receive the maximum sequence number that the wounded measure the relevant amount of equaling that equals constraint condition with the reception node;

m _lMeasure relevant maximum sequence number for allowing to receive the wounded less than the constraint condition upper limit with the reception node;

m _sMeasure relevant maximum sequence number for allowing to receive the wounded greater than the constraint condition lower limit with the reception node;

S _eFor allowing to receive the relevant amount (e=n of wounded's quantity with the reception node _s+ 1 ..., m _e) (unit: the people);

S _lFor allowing to receive the relevant upper limit (l=m of wounded's quantity with the reception node _e+ 1 ..., m _l) (unit: the people);

S _sFor allowing to receive the relevant lower limit (S=m of wounded's quantity with the reception node _i+ 1 ..., m _s) (unit: the people);

V _iFor arrive to receive wounded's node i (i=1 ... m) the means of transport quantity of transporting the wounded;

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

C transports the wounded'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 each and transport wounded's quantity x that node must transport to the correlation reception node _Ij,, can calculate and arrive the means of transport quantity V that each receives node again according to the dead weight capacity L of means of transport _tAnd the means of transport quantity of transporting the node needs, at last transport the wounded's speed C and at the longest path that receives and transport between the node according to means of transport, can calculate again and finish the whole wounded and transport the spent shortest time T of task, thereby realize commander's control to battlefield wounded's rapid transport, 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 shadow price of transporting and receive wounded's constraint condition or the relevant decision variable of opportunity cost with former linear programming;

Since primal linear programming solves be with transport node j and receive node 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 transport node j and receive node 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 _uThe making just of reflection transport node j and receive node 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, 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, but it is also just difficult more to satisfy this condition, therefore, introducing shadow price just can be by comparing shadow price and realistic objective functional value, and can variation that study former linear programming constraint condition make objective function obtain gain.

9, commander's control method of battlefield according to claim 1 wounded's rapid transport, it is characterized in that described this method is according to the length from different take over partys to the difference side of transporting wounded transportation route, the without hindrance transportation probability of transportation route, the take over party wounded's the quantities received and the side of the transporting wounded's upwards of movement, the speed of means of transport and carrying capacity, structure is commander's controlling models of target to transport all wounded 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 battlefield wounded's rapid transport 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 wounded transport T.T., carry out reasonable disposition by the quantity that take over party's permission is received the wounded again, 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. of finishing battlefield wounded transhipment, 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 the commander's control to all battlefield wounded's rapid transports

Suppose that certain mechanization combat division must be that 16 people, average speed per hour are wounded's transfer car(buggy) of 70 kilometers with dead weight capacity, transport the battlefield wounded that a little transport from 6 acceptance points receptions from 14, receive and transport a little between the bound of length, quantities received and upwards of movement of transportation route as shown in table 1, make the without hindrance transportation Probability p of all transportation routes here _Ij(t) be 1, d _Ij=r _Ij/ p _Ij(t), therefore difference receive and the side of transporting between actual shipment path and equivalent transportation route equal in length, i.e. r _IjWith d _IjEquate,

Table 1: the battlefield wounded receive and transport a little between transportation route length, reception and upwards of movement (unit: kilometer, people) 01 acceptance point 02 acceptance point 03 acceptance point 04 acceptance point 05 acceptance point 06 acceptance point Transport the upper limit Transport lower limit 01 transports a little 02 transports a little 03 and transports a little 04 and transport a little 05 and transport a little 06 and transport a little 07 and transport a little 08 and transport a little 09 and transport a little 10 and transport a little 11 and transport a little 12 and transport a little 13 and transport a little and 14 transport a little 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 40.00 60.00 16.00 29.00 36.00 80.00 20.00 25.00 22.00 Can connect limit 100.00 200.00 300.00 400.00 150.00 350.00 Can connect 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, it is as shown in table 2 that the minimum time wounded of mechanization combat division that calculate by simplex algorithm transport option control command,

Table 2: the minimum time wounded of mechanization combat division transport option control command (unit: people, passenger-kilometer,, minute) 01 acceptance point 02 acceptance point 03 acceptance point 04 acceptance point 05 acceptance point 06 acceptance point Passenger-kilometer Fortune car number Need the time Upper limit shadow valency Lower limit shadow valency 01 transports a little 02 transports a little and 03 transports a little 30.00 36.00 60.00 21.00 468.00 399.00 2430.00 3 2 6 11.14 16.29 24.00 13.00 19.00 25.00 13.00 19.00 25.00 04 transports a little 05 transports a little 06 and transports a little 07 and transport a little 08 and transport a little 09 and transport a little 10 and transport a little 11 and transport a little 12 and transport a little 13 and transport a little and 14 transport a little 70.00 64.00 40.00 60.00 36.00 80.00 22.00 29.00 20.00 25.00 66.00 16.00 2940.00 1820.00 800.00 720.00 480.00 725.00 1656.00 1360.00 540.00 275.00 440.00 9 5 3 4 1 2 3 5 2 2 2 25.71 22.29 17.14 10.29 25.71 21.43 39.43 14.57 23.14 9.43 17.14 14.00 26.00 20.00 12.00 30.00 25.00 37.00 0.00 0.00 0.00 0.00 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 ^* Can connect quantity 100.00 200.00 300.00 400.00 150.00 350.00 Connect 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

* finishing the minimum time that the transhipment task expends is 39.43 minutes

By option control command (table 2) is analyzed as can be known; wounded's transfer car(buggy) that finishing the transhipment task needs adds up to 49; time is 39.43 minutes; wounded's transfer car(buggy) that 01～06 acceptance point receives is respectively 11; 16; 14; 2; 4 and 12; therefore must be to 02; 03 and 06 acceptance point is implemented to lay special stress on protecting; further analyze as can be known; transporting 36 39.43 minutes that the wounded spent of a little transporting from the reception of 03 acceptance point from 10 is the bottleneck that the whole transhipment task of restriction is finished sooner; if finish this part wounded's transhipment with helicopter; then can be shortened to 25.71 minutes the time that whole transport task is finished; reduction is 34.80%

From to upwards of movement 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, 10 transport and a little transported the wounded 39.43 minutes consuming time, and the shadow price of this constraint condition is a maximal value 37, illustrates that this condition is the most difficult to satisfy, 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 quantities received 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

In addition, from finish the work the back each acceptance point the residue quantities received as can be seen, the permission quantities received of 02 acceptance point exhausts, and is obviously on the low side, and the permission quantities received of 04 acceptance point is obviously bigger than normal, according to the antithesis analysis, the shadow price of their constraint condition is 0, this statement of facts: if 02 acceptance point has more permission quantities received, 04 acceptance point has permission quantities received still less, just may obtain better diversion 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 of the minimum time transhipment of obtaining is as shown in table 3,

Table 3: the improvement project (unit: people, passenger-kilometer,, minute) of mechanization combat division minimum time transhipment 01 acceptance point 02 acceptance point 03 acceptance point 04 acceptance point 05 acceptance point 06 acceptance point Passenger-kilometer Fortune car number Need the time Upper limit shadow valency Lower limit shadow valency 01 transports a little 02 transports a little 03 and transports a little 04 and transport a little 05 and transport a little 06 and transport a little 07 and transport a little 08 and transport a little 09 and transport a little 10 and transport a little 11 and transport a little 12 and transport a little 13 and transport a little and 14 transport a little 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 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 ^* Can connect quantity 100.00 400.00 300.00 200.00 150.00 350.00 Connect 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 the transhipment task needs

Analysis by his-and-hers watches 3 as can be known, the time that finishing the transhipment 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 allow the wounded that receive to carry out reasonable configuration to each acceptance point, realize allowing the Optimal Management of quantities received with said method.