Resource object planning optimizing distribution of combined operation information war
Resource object planning optimizing distribution of combined operation information war
 CN 1,818,952 A
 Filed: 03/15/2006
 Published: 08/16/2006
 Est. Priority Date: 03/15/2006
 Status: Active Application
First Claim
1. , the present invention relates to the information war resource object planning optimizing distribution of combined operation, relate to military affairs and association area, the optimum allocation object is the information war resource of combined operation, this method at first defines the distribution of information war resource and the fighting capacity attribute of information war resource, construct then the information war resource is carried out distribution criterion, and according to index to information war fighting capacity demand, foundation is to the model of information war resource optimum allocation, and find the solution this model with The goal programming method, the final optimal distributing scheme that obtains according to demand the information war resource, this method has efficiently, simply, objective, characteristics are widely used and obviously improve its combat capabilities etc., can be widely used in the optimum allocation of the information war resource of all combined operation, the invention further relates to the technology that realizes this method.
Chinese PRB Reexamination
Abstract
A information war resource aim programming most superior assign method of combined operations, belongs to the military and the correlative field, the object of the most superior assignment is the information war resource of the combined operations, the method is: define the property of the information war resource assignment and the information war battle effectiveness, construct the assignment rules of the information war resource, setup the model of the most superior assignment of the information war resource according to the battle effectiveness needing guideline of the information war resource, use the aim programming method to find the module, finally get the most superior assignment project according to the needing of the information war resource. The characteristics of the method is higheffective, simple, objective, wide application and improving the battle effectiveness markedly, the method can widely use for the most superior assignment of the combined operations information war resource.

1 Citation
For assisting the flow management method and system of hospital financial budget allocation decision  
Patent #
CN 109,409,593 A
Filed 10/17/2018

Current Assignee

No References
8 Claims

1. , the present invention relates to the information war resource object planning optimizing distribution of combined operation, relate to military affairs and association area, the optimum allocation object is the information war resource of combined operation, this method at first defines the distribution of information war resource and the fighting capacity attribute of information war resource, construct then the information war resource is carried out distribution criterion, and according to index to information war fighting capacity demand, foundation is to the model of information war resource optimum allocation, and find the solution this model with The goal programming method, the final optimal distributing scheme that obtains according to demand the information war resource, this method has efficiently, simply, objective, characteristics are widely used and obviously improve its combat capabilities etc., can be widely used in the optimum allocation of the information war resource of all combined operation, the invention further relates to the technology that realizes this method.

2. the information war resource object planning optimizing distribution of combined operation according to claim 1, it is characterized in that information war resource that described optimum allocation object is combined operation is meant the information war resource of the combined operation object as optimum allocation, actual demand according to region of war or operation, optimum allocation partial information war resource is given region of war or operation from this object, what promptly solve is according to actual needs, optimum allocation partial information war problem of resource from overall information war resource.

3. the information war resource object planning optimizing distribution of combined operation according to claim 1, when it is characterized in that information war resource that described optimum allocation object is combined operation is meant the optimum allocation of research information war resource, usually must consider information war resource and information war resource specific implementation or and the relation of information war between equipping, because the information war equipment is the specific implementation form of information war resource, difference according to the fighting capacity attribute of information war resource itself, the information war equipment can be regarded as by physical equipment, the information war unit that the tactics of related personnel and employing are formed, therefore, to the optimum allocation of information war resource, in fact be exactly optimum allocation to information war equipment itself.

4. the information war resource object planning optimizing distribution of combined operation according to claim 1, the fighting capacity attribute that it is characterized in that described distribution that at first defines the information war resource and information war resource is meant in the part of resource that overall information is fought distributes to the region of war, when operation or other object, think that the information war resource has multiple fighting capacity or has multiple fighting capacity attribute, and the percentage that is used in different information war fighting capacity contained in the unit information war resource comes the information war fighting capacity attribute of quantitative description information war resource, be that the information war resource is a kind of resource with multiple information war fighting capacity or fighting capacity attribute, this also is the important foundation that the information war resource can be carried out optimum allocation.

5. the information war resource object planning optimizing distribution of combined operation according to claim 1, it is characterized in that described the structure then carry out distribution criterion to the information war resource and be meant that distribution portion information war resource is carried out according to some predetermined criteria or rule from overall information war resource, the distribution of satisfying these criterions or rule to greatest extent is also referred to as optimum allocation, and the functional form of these criterions or rule is called the objective function of implementing optimum allocation, and can set up different criterions or rule according to actual needs on their own, for example:
 in order to guarantee most economical use to overall information war resource, can set up the minimum cost objective function relevant with " most economical using priciple " and implement optimum allocation, promptly distribution portion information war resource is finished as target by predetermined criteria or rule from overall information war resource.

6. the information war resource object planning optimizing distribution of combined operation according to claim 1, it is characterized in that described and according to index to information war fighting capacity demand, foundation is meant concerning a side of information war resource requirement the model of information war resource optimum allocation, can be according to the actual demand of its region of war, place or operation, proposition (can be passed through Combat Simulation usually to the specific requirement of information war fighting capacity, experimental formula or other any way are determined the real needs to information war fighting capacity), these demands are then in the optimum allocation of information war resource, be used as the constraint condition that optimum allocation must be satisfied, and then on the basis of the constraint condition of the objective function of optimum allocation and optimum allocation, the model of structure implementation information war resource optimum allocation, promptly having the objective function of optimum allocation and the constraint condition of optimum allocation is the key character of information war resource optimal allocation model.

7. the information war resource object planning optimizing distribution of combined operation according to claim 1, it is characterized in that described and find the solution this model with The goal programming method, the final optimal distributing scheme that obtains according to demand the information war resource is meant and following the information war resource is carried out the goal programming equation of optimum allocation and by finding the solution the optimal distributing scheme of the information war resource that this equation obtains, but following mathematical formulae, derivation, result of calculation and application process are applicable to the optimum allocation to the information war resource of all combined operation
For specific operation pattern;  Can be in the hope of in the information war resource that needs in this pattern;
Various fighting capacity resources are shared best proportion in total information war resource;
And then according to this best proportion;
Whole information war resource is carried out allocation optimum;
Therefore also can be with the optimal assignment problem of information war resource;
Regard the optimization formula problem of various fighting capacity resources in the information war resource as;
The planning of information war resource object or multiobjective linear programming optimum allocation method can further describe as followsDefinition x _{i}(i=1 ..., n) decision variable, a for information war resource i is carried out optimum allocation _{Ij}Be the information war resource _{i}Contain fighting capacity _{j}(j=1 ..., quantity m), b _{j}The of the information war resource of distributing for hope _{j}The Index of Combat Effectiveness that individual fighting capacity attribute reaches, c _{i}Be the information war resource _{i}Price, then definable constitutes, is used for linear programming model that n information war resource carried out optimum allocation by objective function and constraint system of equations;
Objective function MinZ is the cost minimization that makes the information war resource; MinZ＝
c _{1}x _{1}+…
+c _{n}x _{n}The equation of constraint group is; a _{11}x _{1}+a _{12}x _{2}+…
+a _{1n}x _{n}≥
b _{1}(＝
，
≤
b _{1})a _{21}x _{1}+a _{22}x _{2}+…
+a _{2n}x _{n}≥
b _{2}(＝
，
≤
b _{2})… a _{m1}x _{1}+a _{m2}x _{2}+…
+a _{mn}x _{n}≥
b _{m}(＝
，
≤
b _{m})x _{1}≥
0，
x _{2}≥
0，
…
，
x _{n}≥
0Find the solution abovementioned linear programming model by simplex algorithm, can obtain the optimum allocation result or the prescription of information war resource, therefore, 5 condition precedents using linear programming and multiobjective linear programming in the optimum allocation of information war resource are; (1) severability The information war resource (decision variable) that all are assigned with can resolve into the significant part of any size or be made up of the significant part of any size, can resolve into different information war fighting capacity partly or by different information war fighting capacity part institutes is formed (2) direct proportion For aritrary decision variable x _{i}, its contribution to cost is c _{i}x _{i}, be a to the contribution of j kind fighting capacity _{Ij}x _{i}If, with x _{i}Amount double, also should double to cost or to the contribution of fighting capacity composition so, (3) additive property The total cost of the information war resource of distributing is the cost sum of each information war resource, and the information war resource of distribution is the contribution sum of a plurality of information war resources to total contribution of j constraint, (4) consistency of axioms In linear programming, should there be mutual repellency between the information war resource of Fen Peiing together, cooperation together, (5) nonrandomness All c _{i}, a _{Ij}And b _{j}All be known, deterministic, rather than at random, Yet, although this linear programming method is simple, there is following shortcoming; (1) has only single optimal objective, can'"'"'t take into account a plurality of optimal objectives; (2) be easy to occur not having the situation of separating; (3) only be the optimum solution of mathematics, rather than the satisfactory solution of practical problems; (4) solving result is single, can'"'"'t screen a plurality of solving results; (5) the fighting capacity demand of constraint condition is fixed, can'"'"'t the particular requirement of multiple factor be retrained, Usually the primal linear programming that abovementioned linear programming is called multiobjective linear programming, multiobjective linear programming model is to be based upon on the abovementioned primal linear programming model based, but overcome the deficiency of primal linear programming model, can not only effectively handle the contradiction that exists each other at constraint condition and objective function, but also can solve multiobjective optimization question, following rule is followed in the optimization of target; (1) according to priority height order is optimized a plurality of targets, is prerequisite with the optimal value that does not destroy high level goal during rudimentary objective optimization; (2) be in different target on the same priority, be optimized by the weight coefficient size, So just can be according to the demand of information war fighting capacity and decisionmaker'"'"'s subjective desire;
Method with mathematics;
All targets that need to optimize are different by its importance degree;
Be divided into different priority;
Different target on the equal priority gives different weights;
This is because when carrying out information war resource optimum allocation calculating;
The importance of relevant a plurality of targets may be different;
So must determine as the case may be priority and the weight of each target;
And the foundation of carrying out the optimum allocation of information war resource as the goal programming systemOn abovementioned primal linear programming model based, the mathematical model of structure multiobjective linear programming is as follows, Be provided with n decision variable x _{j}(j=1,2 ..., n), the goal programming problem of L priority is arranged in the k goal constraint, a m system restriction, objective function, its general form is;
Objective function;
$\mathrm{min}Z=\underset{}{\overset{}{\mathrm{\Σl=1L{\mathrm{rho;l\underset{}{\overset{}{\mathrm{Sigma;k=1k({w}_{\mathrm{lk}}^{}{n}_{k}+{w}_{\mathrm{lk}}^{+}{p}_{k})}}}}}_{}}}}$ Goal constraint;
$\underset{}{\overset{}{\mathrm{\Σj=1n{c}_{\mathrm{kj}}{x}_{j}+{n}_{k}{p}_{k}={g}_{k},}}}$ (k＝
1，
2，
…
，
k)System restriction;
$\underset{}{\overset{}{\mathrm{\Σj=1n{a}_{\mathrm{ij}}{x}_{j}le;(=,GreaterEqual;){b}_{i},}}}$ (i＝
1，
2，
…
，
m)Nonnegativity restrictions;
x _{j}〉
=0, (i=1,2 ..., n);
n _{k}, p _{k}〉
=0In the formula; x _{j}decision variable;
a _{Ij}system restriction coefficient;
c _{Kj}goal constraint coefficient;
b _{i}The righthand member constant ofDi i constraint;
g _{k}The expectation value an ofDi k goal constraint;
ρ
_{l}The priority level ofgoal constraint (the preferential factor);
w _{Lk}^{}ρ
_{l}N in the level target _{k}Weight coefficient;
w _{Lk}^{+}ρ
_{l}P in the level target _{k}Weight coefficient;
n _{k}, p _{k}Be deviation variables, According to the above discussion, multiobjective linear programming comes down to mathematical model with multiobjective linear programming and is converted into ordinary lines part plan model and finds the solution, and therefore, the general step of finding the solution multiobjective linear programming model is as follows; The first step;
set up linear programming model (comprise the hypothesis decision variable, set up equation or inequality constrain condition, set up relevant processes such as objective function) according to practical problems with m target,Second step;
multiobjective linear programming model is converted into single goal or general linear programming model;(1), determine suitable expectation value g for k target according to practical problems _{k}(k=1,2 ..., k);
(2) k target introduced n _{k}, p _{k}, set up the goal constraint equation and it listed among the former constraint condition;
(3) if in the former constraint condition conflicting equation is arranged, then to they same n that introduces _{k}And p _{k}, more generally way is that all equation of constraint are all introduced n _{k}And p _{k} (4) determine the priority level ρ
of k target _{l}And weight coefficient w _{Lk}^{}And w _{Lk}^{+}(5) set up the objective function minZ that will reach, After finishing abovementioned steps, just can set up linear goal planning, find the solution with simplex method then with general lexicographic order or priority.
 Can be in the hope of in the information war resource that needs in this pattern;

8. the information war resource object planning optimizing distribution of combined operation according to claim 1, it is characterized in that described and find the solution this model with The goal programming method, the final optimal distributing scheme that obtains according to demand the information war resource is meant that the former veneziano model that carries out the Goal programming Model of information war resource optimum allocation can be used to analyze the satisfaction degree of Index of Combat Effectiveness of primal linear programming model to the influence of the satisfaction degree of objective function, promptly be used for determining of the influence of the satisfaction degree of Index of Combat Effectiveness to the satisfaction degree of objective function, following mathematical formulae, derivation, result of calculation and application process are applicable to the antithesis analysis to the optimum allocation of the information war resource of all combined operation
By analysis to the dual program of abovementioned primal linear programming, can study the economic cost of each fighting capacity binding target in the primal linear programming problem, this cost is also referred to as shadow price, optimal assignment problem for the information war resource, by finding the solution its dual problem, can carry out following quantitative test: 
(1) can calculate the real economy of various information war resources in optimum allocation or optimization formula according to shadow price is worth, obviously, all information war resources that is selected into optimum allocation or optimization formula, inevitable war (city) price of its economic worth more than or equal to it, otherwise, this information war resource will fail to be elected, therefore the decision maker can judge, when which kind of level is the price of selected information war resource rise to, the proportioning of this information war resource will descend even can not continue use in relevant optimum allocation or the optimization formula, and which kind of level unelected information war resource price when dropping to, and will be selected into optimum allocation will make a profit certainly (2) provide the price effective range of the various information war resources of forming optimum allocation, when the price of information war resource changes in this scope, the optimum allocation result will remain unchanged, in case the price of information war resource surpasses its effective range, then need to carry out again optimum allocation, minimum to guarantee cost (3) valid interval of calculating Index of Combat Effectiveness, the shadow price of multiple Index of Combat Effectiveness is constant in this is interval, this moment, Index of Combat Effectiveness reduced a unit value, the information war resources costs reduction value of distributing equals the shadow price of this fighting capacity composition, the decision maker can seek certain information war resource that the effective way that reduces cost or selection have economic benefit in view of the above For veneziano model by the primal linear programming model, further analyze the architectural feature of separating of abovementioned primal linear programming model, definition is the decision variable y that describes m fighting capacity key element by objective function and constraint system of equations veneziano model that constitute, abovementioned primal linear programming model _{j}(j=1 ..., linear programming model m);
Objective function MaxG reaches maximization for making the fighting capacity content'"'"'s index; MaxG＝
b _{1}y _{1}+…
+b _{m}y _{m}The equation of constraint group is; a _{11}y _{1}+a _{21}y _{2}+…
+a _{m1}y _{m}≤
c _{1}a _{12}y _{1}+a _{22}y _{2}+…
+a _{m2}y _{m}≤
c _{2}… a _{1n}y _{1}+a _{2n}y _{2}+…
+a _{mn}y _{m}≤
c _{m}y _{1}≥
0，
y _{2}≥
0，
…
，
y _{m}≥
0Decision variable y wherein _{j}(j=1,2 ..., m) for waiting to ask the Index of Combat Effectiveness b of information war resource _{j}(j=1,2 ..., shadow price m) or opportunity cost, Find the solution abovementioned dual linear programming model by simplex algorithm, can finish antithesis analysis abovementioned primal linear programming.

Specification(s)