CN103942647A - Emergency resource scheduling method oriented towards complicated supply mode - Google Patents

Abstract

The embodiment of the invention provides an emergency resource scheduling method oriented towards a complicated supply mode. According to the emergency resource scheduling method, a matrix mode is used for carrying out individual coding on complicated many-to-many source scheduling, an emergency resource scheduling strategy is worked out according to the requirement for the varieties and the number of related emergency resources in an emergency area, supply points participating in emergency resource rescue are selected, and loss is reduced to be minimum as much as possible. The emergency resource scheduling method oriented towards the complicated supply mode is applicable to emergency resource scheduling of multiple emergency resource reserve points and diverse resource supply modes in a complicated reserve system and a complicated reserve network layout.

Description

A kind of emergency resources dispatching method towards complicated supply model

Technical field

The present invention relates to areas of information technology, be specifically related to a kind of emergency resources dispatching method towards complicated supply model.

Background technology

Nowadays, on the earth that the mankind depend on for existence and live, various accidents are just presenting the highly trend of unconventionalization, never occur in history or a-hundred-year accident and disaster, but occur more and more frequently now.In the face of various disasteies, emergency resources guarantee is the condition precedent of launching accident emergency management and rescue, requires certain area or trans-regional resource to rationalize layout and dynamically allotment, to the rapid Optimum scheduling of all kinds of emergency resources of overall importance.

The top priority of solution of emergent event is that the loss that accident is caused is reduced to minimum, towards the emergency resources delivery system of this complexity, the emergency resources that how effectively scheduling source is various, kind is numerous and jumbled, quantity is huge, to meet disaster area rescue demand, and as much as possible by casualty loss and rescue cost control in minimum, be in face of problem demanding prompt solution.

Summary of the invention

The embodiment of the present invention provides a kind of emergency resources dispatching method towards complicated supply model, to the effectively emergency resources scheduling towards complicated supply model is provided, meanwhile, farthest by the loss of accident and rescue cost control in minimum.

First aspect, the embodiment of the present invention provides a kind of emergency resources dispatching method towards complicated supply model, and described method comprises:

Initialization population: the emergency resources individuality in population S is carried out to matrix coder,

$S=\left[\begin{array}{cccccc}{x}_{11}& x_{12}& ...& x_{1j}& ...& x_{1m}\\ x_{21}& x_{22}& ...& x_{1j}& ...& x_{2m}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{i1}& x_{i2}& ...& x_{\mathrm{ij}}& ...& x_{\mathrm{im}}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{n1}& x_{n2}& ...& x_{\mathrm{nj}}& ...& x_{\mathrm{nm}}\end{array}\right]$

Wherein, n represents that total n emergency resources feed point participates in this emergency resources scheduling, and m represents that total m kind emergency resources need be dispatched to disaster area, 1≤i≤n, 1≤j≤m, x _ijrepresent to dispatch the quantity of j kind emergency resources to disaster area from i emergency resources feed point;

Calculate the loss value of each individuality in population according to default least disadvantage function,, wherein said least disadvantage refers to the least disadvantage min F causing due to the j kind emergency resources lacking in population S,

$\begin{array}{c}\min F=\mathrm{\α}{\mathrm{\Σ}}_{j=1}^m{\mathrm{\Σ}}_{i=1}^n{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\β}{\mathrm{\Σ}}_{j=1}^m{\mathrm{Loss}}_j=\\ \left\{\begin{array}{c}\mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{i\; j}}{x}_{\mathrm{ij}}+\mathrm{\β}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}(U_j{C}_{i+1,j}(v_j(t_i-t_1)-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}})(t_{i+1}-t_i)+1/{2v}_j(t_{i+1}^2-t_i^2)),\\ \mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\β}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\left(\frac{1}{2}{v}_j{U}_j{C}_{i+1,j}(t_{i+1}^2-{(\frac{1}{v_j}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}+t_1)}^2)\right),\\ \mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}},\end{array}\right.\end{array}$

And meet

Wherein, v _jrepresent that emergency management and rescue start the spending rate of rear j kind emergency resources, U _jrepresent to lack in each unit interval the loss that the j kind emergency resources of a unit causes, C _ijrepresent that the j kind emergency resources of a unit is from i the emergency resources feed point transportation cost required to disaster area, α and β represent weight adjusting knob, and are positive number;

Carry out selection operation, interlace operation and the mutation operation of emergency resources individuality, until meet end condition.

Further, in calculating population according to default least disadvantage function, comprise when the loss value of each individuality:

If at t _iin the moment, the j kind emergency resources in disaster area has been exhausted, the loss causing in default of j kind emergency resources

$\begin{array}{c}{\mathrm{Loss}}_j=-U_j{C}_{i+1,j}{\∫}_i^{i+1}[Q_j\left(t_i\right)-v_{j}t]\mathrm{dt}\\ =-U_j{C}_{i+1,}j[Q_j\left(t_i\right)(t_{i+1}-t_i)-1/{2v}_j(t_{i+1}^2-t_i^2)\end{array}$

Wherein, Q _j(t _i) be at t _ithe j kind emergency resources volume residual in moment disaster area, $Q_j\left(t_i\right)={\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}-$ $v_j(t_i-t_1);$

If at t _iin the ˊ moment, the j kind emergency resources in disaster area is exhausted, wherein t ' _i∈ [t _i, t _i+1), Q _j(t _i)-v _j(t ' _i-t ₁)=0, (i=1,2 ..., n, j=1,2 ... m), due to $Q_j\left(t_i\right)={\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}-$ $v_j(t_i-t_1),$ So $t_i^{\′}=\frac{1}{v_j}{\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}+t_1,$ Thereby

$\begin{array}{c}{\mathrm{Loss}}_j=U_j{C}_{i+1,j}+{\∫}_i^{i+1}{v}_j\mathrm{tdt}=\frac{1}{2}{v}_j{U}_j{C}_{i+1}(t_{i+1}^2-t_i^{\′2})\\ =\frac{1}{2}{v}_j{U}_j{C}_{i+1,j}(t_{i+1}^2-{(\frac{1}{v_j}{\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}+t_1)}^2);\end{array}$

If at t _i+1in the moment, the j kind emergency resources in disaster area is not exhausted, Loss _j=0.

Further, the selection operation of carrying out emergency resources individuality described in comprises:

Least disadvantage value to all emergency resources individualities sorts according to size, the difference of preferably loss value and differential loss mistake value is divided into M hierarchical region, loss is worth to best individuality and directly inserts progeny population, remaining individuality is dispensed to corresponding hierarchical region according to least disadvantage value separately; ;

Calculate the average minimum loss value A1 of each hierarchical region, described A1 is that the least disadvantage value sum of each individuality in current hierarchical region is divided by the individual amount of this grade district inclusion;

Carry out roulette for the first time and select operation, the average minimum loss value A1 that the selected probability B1 of each hierarchical region is current hierarchical region is divided by the average fitness value sum of all hierarchical regions;

Carry out roulette for the second time and select operation, calculate the selected probability B2 of each individuality in each hierarchical region, described B2 is the fitness sum of this individual fitness value divided by all individualities of current hierarchical region; Calculate the selected probability B3 of each individuality in population S, B3 equals B1 and is multiplied by B2.

The described interlace operation of carrying out emergency resources individuality comprises:

A point of crossing j of random selection, individual the parent of matrix coder Parent1 and Parent2 are divided into respectively to two parts, Parent1 is cut apart to the part that obtains and Parent2 and cut apart the corresponding part obtaining and carry out coordinated transposition, thereby obtain two new offspring individuals.

Wherein, the selection operation of carrying out emergency resources individuality described in comprises:

From the root node of y-bend space cut tree, belong to left sibling space or right node space according to first pre-conditioned definite xij, and continue search downwards along the node direction of subspace, place, till searching leaf node;

If first front nodal point does not repeat in described xij and y-bend space cut tree, directly insert y-bend space cut tree, as new leaf node; Wherein, if described x _ijfather node without left child node, described xij directly inherits his father's node searching subspace as left child node, if described x _ijthe existing left child node x of father node _ij, according to the second pre-conditioned position adjustment of carrying out left child node and right child node;

If described x _ijwhen inserting y-bend space cut tree and having carried out subspace cutting operation, the left child node after inspection is cut apart and right child node search volume, whether in indivisible state, if so, arrange described x _ijposition is closed condition.

Based on this, further, described in carry out emergency resources individuality mutation operation comprise:

If inserting the individual x of new chromosome _rztime there is x _rzwith x _ijrepeat, wherein 1≤r≤n, 1≤z≤m, at x _ijthe search subspace Subspace(x shining upon _ij) in scope to x _rzcarry out mutation operation, or at Subspace(x _ij) neighborhood within the scope of to x _rzcarry out mutation operation, or be not subject to Subspace(x _ij) restriction of scope is to S(j) carry out mutation operation.

Concrete, inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, at x _ijthe search subspace Subspace(x shining upon _ij) in scope to x _rzcarrying out mutation operation comprises:

Determine Subspace(x _ij) whether the position of the switch be open state, if so, works as x _ijleft child node or right child node be empty, select Subspace(x _ij) gene position of dimensional space maximum, x _rzat described Subspace(x _ij) genetic mutation is carried out in the corresponding gene position of selecting within the scope of dimensional space; If the x after variation _rzstill with x _ijidentical, stop x _rzcarry out again mutation operation.

Inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, at Subspace(x _ij) neighborhood within the scope of to x _rzcarrying out mutation operation comprises:

Determine described x _ijthe search subspace Subspace(x shining upon _ij) whether the position of the switch be closed condition, if so, rollback to described x _ijfather node, and judge described x _ijbrotgher of node x _pqthe search subspace Subspace(x shining upon _pq) whether the position of the switch be open state, if so,

Scan the individual x of new chromosome _rzeach gene whether belong to Subspace(x _pq), by the gene not belonging at Subspace(x _pq) carry out random variation in corresponding dimensional space.

Inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, be not subject to Subspace(x _ij) restriction of scope is to x _rzcarrying out mutation operation comprises:

Determine described x _ijleft child node space and right child node space whether be closed condition, if so,

The individual x of new chromosome _rzgene random variation in its original dimensions spatial dimension be x _rzˊ, from the root node search x of y-bend space cut tree _rzaffiliated node subspace.

The scheduling of the emergency resources towards complicated supply model that the embodiment of the present invention provides, take, by matrix-style, complicated multi-to-multi scheduling of resource is carried out to individuality coding, and make emergency resources according to the demand of relevant emergency resources kind and quantity in accident region and allot strategy, select to participate in the feed point of emergency resources rescue, loss is dropped to minimum, the method is applicable to the emergency resources of many emergency resources deposit point and diversified resource provision pattern under complicated deposit system and deposit network topology dispatches as far as possible.

Brief description of the drawings

Fig. 1 is a kind of emergency resources dispatching method schematic flow sheet towards complicated supply model that the embodiment of the present invention provides;

Fig. 2 is a kind of socialization emergency resources delivery system structural representation that the embodiment of the present invention provides;

Fig. 3 is the optimization method schematic flow sheet of selecting based on roulette that the embodiment of the present invention provides;

Fig. 4 (1) is two individual schematic diagram of the emergency resources of utilizing matrix to encode that the embodiment of the present invention provides;

Fig. 4 (2) is the schematic diagram after the emergency resources individuality in Fig. 4 (1) that the embodiment of the present invention provides is cut apart;

Fig. 4 (3) is the new chromosome individuality obtaining after two emergency resources individualities to Fig. 4 (2) that the embodiment of the present invention provides intersect.

Embodiment

The embodiment of the present invention provides a kind of emergency resources dispatching method towards complicated supply model, to the effectively emergency resources scheduling towards complicated supply model is provided, meanwhile, farthest by the loss of accident and rescue cost control in minimum.

In order to make those skilled in the art person understand better the present invention program, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the embodiment of a part of the present invention, instead of whole embodiment.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtaining under creative work prerequisite, should belong to the scope of protection of the invention.

The embodiment of the present invention provides a kind of emergency resources dispatching method towards complicated supply model, comprising:

Initialization population: the emergency resources individuality in population S is carried out to matrix coder,,

$S=\left[\begin{array}{cccccc}{x}_{11}& x_{12}& ...& x_{1j}& ...& x_{1m}\\ x_{21}& x_{22}& ...& x_{1j}& ...& x_{2m}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{i1}& x_{i2}& ...& x_{\mathrm{ij}}& ...& x_{\mathrm{im}}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{n1}& x_{n2}& ...& x_{\mathrm{nj}}& ...& x_{\mathrm{nm}}\end{array}\right]$

Wherein, n represents that total n emergency resources feed point participates in this emergency resources scheduling, and m represents that total m kind emergency resources need be dispatched to disaster area, 1≤i≤n, 1≤j≤m, x _ijrepresent to dispatch the quantity of j kind emergency resources to disaster area from i emergency resources feed point;

Calculate the loss value of each individuality in population according to default least disadvantage function,, wherein said least disadvantage refers to the least disadvantage min F causing due to the j kind emergency resources lacking in population S,

$\mathrm{mniF}=\mathrm{\α}{\mathrm{\Σ}}_{j=1}^m{\mathrm{\Σ}}_{i=1}^n{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\β}{\mathrm{\Σ}}_{j=1}^m{\mathrm{Loss}}_j=$

$\left\{\begin{array}{c}\mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\β}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\left(U_j{C}_{i+1,j}((v_j(t_i-t_1)-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}})(t_{i+1}-t_i)+1/{2v}_j(t_{i+1}^2-t_i^2))\right),\\ \mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\β}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\left(\frac{1}{2}{v}_j{U}_j{C}_{i+1,j}(t_{i+1}^2-{(\frac{1}{v_j}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}+t_1)}^2)\right),\\ \mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}},\end{array}\right.$

And meet

Wherein, v _jrepresent that emergency management and rescue start the spending rate of rear j kind emergency resources, U _jrepresent to lack in each unit interval the loss that the j kind emergency resources of a unit causes, C _ijrepresent that the j kind emergency resources of a unit is from i the emergency resources feed point transportation cost required to disaster area, α and β represent weight adjusting knob, and are positive number;

Carry out selection operation, interlace operation and the mutation operation of emergency resources individuality, until meet end condition.

Wherein, α and β are weight adjusting knob, with adaptive surface to old under emergency circumstances of different nature and loss assessment, especially in face of great especially accident, save disaster area people life property loss and ensure that disaster area common people's daily life need to be primary liability, β can be tuned up as far as possible, such as being greater than 0.5.

The default least disadvantage function of described basis calculates the loss value of each individuality in population, and wherein said least disadvantage refers to that the least disadvantage min F causing due to the j kind emergency resources lacking in population S specifically comprises:

If at t _iin the moment, the j kind emergency resources in disaster area has been exhausted, the loss causing in default of j kind emergency resources

$\begin{array}{c}{\mathrm{Loss}}_j=-U_j{C}_{i+1,j}{\∫}_i^{i+1}[Q_j\left(t_i\right)-v_{j}t]\mathrm{dt}\\ =-U_j{C}_{i+1,j}[Q_j\left(t_i\right)(t_{i+1}-t_i)-1/{2v}_j(t_{i+1}^2-t_i^2)\end{array}$

Wherein, Q _j(t _i) be at t _ithe j kind emergency resources volume residual in moment disaster area, $Q_j\left(t_i\right)={\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}-$ $v_j(t_i-t_1);$

If at t _iin the ˊ moment, the j kind emergency resources in disaster area is exhausted, wherein t ' _i∈ [t _i, t _i+1), Q _j(t _i)-v _j(t ' _i-t ₁)=0, (i=1,2 ..., n, j=1,2 ... m), due to $Q_j\left(t_i\right)={\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}-$ $v_j(t_i-t_1),$ So $t_i^{\′}=\frac{1}{v_j}{\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}+t_1,$ Thereby

$\begin{array}{c}{\mathrm{Loss}}_j=U_j{C}_{i+1,j}+{\∫}_i^{i+1}{v}_j\mathrm{tdt}=\frac{1}{2}{v}_j{U}_j{C}_{i+1}(t_{i+1}^2-t_i^{\′2})\\ =\frac{1}{2}{v}_j{U}_j{C}_{i+1},j(t_{i+1}^2-{(\frac{1}{v_j}{\mathrm{\Σ}}_{i=1}^n{x}_{\mathrm{ij}}+t_1)}^2);\end{array}$

If at t _i+1in the moment, the j kind emergency resources in disaster area is not exhausted, Loss _j=0.

The described selection operation of carrying out emergency resources individuality comprises:

Least disadvantage value to all emergency resources individualities sorts according to size, the difference of preferably loss value and differential loss mistake value is divided into M hierarchical region, loss is worth to best individuality and directly inserts progeny population, remaining individuality is dispensed to corresponding hierarchical region according to least disadvantage value separately; ;

Calculate the average minimum loss value A1 of each hierarchical region, described A1 is that the least disadvantage value sum of each individuality in current hierarchical region is divided by the individual amount of this grade district inclusion;

Carry out roulette for the first time and select operation, the average minimum loss value A1 that the selected probability B1 of each hierarchical region is current hierarchical region is divided by the average fitness value sum of all hierarchical regions;

Carry out roulette for the second time and select operation, calculate the selected probability B2 of each individuality in each hierarchical region, the minimum loss value that described B2 is this individuality is divided by the fitness sum of all individualities of current hierarchical region;

Calculate the selected probability B3 of each individuality in population S, B3 equals B1 and is multiplied by B2.

Further, the interlace operation of carrying out emergency resources individuality described in comprises:

A point of crossing j of random selection, individual the parent of matrix coder Parent1 and Parent2 are divided into respectively to two parts, Parent1 is cut apart to the part that obtains and Parent2 and cut apart the corresponding part obtaining and carry out coordinated transposition, thereby obtain two new offspring individuals.

The described selection operation of carrying out emergency resources individuality comprises:

From the root node of y-bend space cut tree, belong to left sibling space or right node space according to first pre-conditioned definite xij, and continue search downwards along the node direction of subspace, place, till searching leaf node;

If described x _ijdo not repeat with first front nodal point in the cut tree of y-bend space, directly insert y-bend space cut tree, as new leaf node; Wherein, if described x _ijfather node without left child node, described xij directly inherits his father's node searching subspace as left child node, if described x _ijthe existing left child node x of father node _ijˊ, according to the second pre-conditioned position adjustment of carrying out left child node and right child node;

If described x _ijwhen inserting y-bend space cut tree and having carried out subspace cutting operation, the left child node after inspection is cut apart and right child node search volume, whether in indivisible state, if so, arrange described x _ijposition is closed condition.

Further, the mutation operation that carries out emergency resources individuality described in comprises:

If inserting the individual x of new chromosome _rztime there is x _rzwith x _ijrepeat, wherein 1≤r≤n, 1≤z≤m, at x _ijthe search subspace Subspace(x shining upon _ij) in scope to x _rzcarry out mutation operation, or at Subspace(x _ij) neighborhood within the scope of xrz is carried out to mutation operation, or be not subject to Subspace(x _ij) restriction of scope is to S(j) carry out mutation operation.

Further, if described at the individual x of the new chromosome of insertion _rztime there is x _rzwith x _ijrepeat, at x _ijthe search subspace Subspace(x shining upon _ij) in scope to x _rzcarrying out mutation operation comprises:

Determine Subspace(x _ij) whether the position of the switch be open state, if so, works as x _ijleft child node or right child node be empty, select Subspace(x _ij) gene position of dimensional space maximum, x _rzat described Subspace(x _ij) genetic mutation is carried out in the corresponding gene position of selecting within the scope of dimensional space; If the x after variation _rzstill with x _ijidentical, stop x _rzcarry out again mutation operation.

Inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, at Subspace(x _ij) neighborhood within the scope of to x _rzcarrying out mutation operation comprises:

Determine described x _ijthe search subspace Subspace(x shining upon _ij) whether the position of the switch be closed condition, if so, rollback to described x _ijfather node, and judge described x _ijbrotgher of node x _pqthe search subspace Subspace(x shining upon _pq) whether the position of the switch be open state, if so,

Scan the individual x of new chromosome _rzeach gene whether belong to Subspace(x _pq), by the gene not belonging at Subspace(x _pq) carry out random variation in corresponding dimensional space.

Inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, be not subject to Subspace(x _ij) restriction of scope is to x _rzcarrying out mutation operation comprises:

Determine described x _ijleft child node space and right child node space whether be closed condition, if so,

The individual x of new chromosome _rzgene random variation in its original dimensions spatial dimension be x _rzˊ, from the root node search x of y-bend space cut tree _rznode subspace under ˊ.

As from the foregoing, the scheduling of the emergency resources towards complicated supply model that the embodiment of the present invention provides, take, by matrix-style, complicated multi-to-multi scheduling of resource is carried out to individuality coding, and make emergency resources according to the demand of relevant emergency resources kind and quantity in accident region and allot strategy, select to participate in the feed point of emergency resources rescue, loss is dropped to minimum, the method is applicable to the emergency resources of many emergency resources deposit point and diversified resource provision pattern under complicated deposit system and deposit network topology dispatches as far as possible.

The embodiment of the present invention provides a kind of emergency resources dispatching method towards complicated supply model, shown in Figure 1, comprising:

S100, initialization population: the emergency resources individuality in population S is carried out to matrix coder,

$S=\left[\begin{array}{cccccc}{x}_{11}& x_{12}& ...& x_{1j}& ...& x_{1m}\\ x_{21}& x_{22}& ...& x_{1j}& ...& x_{2m}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{i1}& x_{i2}& ...& x_{\mathrm{ij}}& ...& x_{\mathrm{im}}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{n1}& x_{n2}& ...& x_{\mathrm{nj}}& ...& x_{\mathrm{nm}}\end{array}\right]$

Wherein, n represents that total n emergency resources feed point participates in this emergency resources scheduling, and m represents that total m kind emergency resources need be dispatched to disaster area, 1≤i≤n, 1≤j≤m, x _ijrepresent to dispatch j emergency resources to the quantity in disaster area from i emergency resources feed point;

It should be noted that, the socialization resources reserve that current China is building with allot in system, emergency resources is supplied with source and is divided into administrative strategies emergency resources deposit site, production enterprise deposit, commercial distribution enterprise, donations resource on-line shop of society etc., and the emergency materials type of different resource feed point is also diversified, shown in Figure 2, Fig. 2 is a kind of socialization emergency resources delivery system structural representation.

In the time that accident occurs, government can make immediately emergency resources according to the demand of relevant emergency resources kind and quantity in accident region and allot strategy, selects to participate in the feed point of emergency resources rescue.

In the face of so complicated many-to-many relationship, various combination sights cannot be described with binary coding and real coding, the present invention program takes matrix coder, carry out individuality coding with matrix, build the random n*m matrix of a mapping space, the simply various combined situation of direct representation, such mode has larger representation space, and each matrix represents a potential scheduling strategy.

S200, calculate the loss value of each individuality in population according to default least disadvantage function, wherein said least disadvantage refers to the least disadvantage min F causing due to the j kind emergency resources lacking in population S:

$\begin{array}{c}\min F=\mathrm{\α}{\mathrm{\Σ}}_{j=1}^m{\mathrm{\Σ}}_{i=1}^n{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\β}{\mathrm{\Σ}}_{j=1}^m{\mathrm{Loss}}_j=\\ \left\{\begin{array}{c}\mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{i\; j}}{x}_{\mathrm{ij}}+\mathrm{\β}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}(U_j{C}_{i+1,j}(v_j(t_i-t_1)-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}})(t_{i+1}-t_i)+1/{2v}_j(t_{i+1}^2-t_i^2)),\\ \mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\β}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\left(\frac{1}{2}{v}_j{U}_j{C}_{i+1,j}(t_{i+1}^2-{(\frac{1}{v_j}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}+t_1)}^2)\right),\\ \mathrm{\α}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}},\end{array}\right.\end{array}$

And meet

Wherein, v _jrepresent that emergency management and rescue start the spending rate of rear j kind emergency resources, U _jrepresent to lack in each unit interval the loss that the j kind emergency resources of a unit causes, C _ijrepresent that the j kind emergency resources of a unit is from i the emergency resources feed point transportation cost required to disaster area, α and β represent weight adjusting knob, and are positive number;

It should be noted that, calculating [t _i, t _i+1] in the time cycle because lack the loss Loss that j kind emergency resources causes _jtime, be divided into following three kinds of situations:

(1) at t _imoment j kind emergency resources is exhausted already, i.e. Q _j(t _i) <0, (i=1,2 ..., n).

Calculate Q by formula (2-1) _j(t _i)::

$Q_j\left(t_i\right)={\mathrm{\&Sigma;}}_{i=1}^n{x}_{\mathrm{ij}}-v_j(t_i-t_1)---(2-1)$

At time cycle [t _i, t _i+1] in

$\begin{array}{c}{\mathrm{Loss}}_j=-U_j{C}_{i+1,j}{\&Integral;}_i^{i+1}[Q_j\left(t_i\right)-v_{j}t]\mathrm{dt}\\ =-U_j{C}_{i+1,}j[Q_j\left(t_i\right)(t_{i+1}-t_i)-1/{2v}_j(t_{i+1}^2-t_i^2)\end{array}---(2-2)$

Formula (2-1) is brought into (2-2),

${\mathrm{Loss}}_j=U_j{C}_{i+1},j((v_j(t_{i+1}-t_i)-{\mathrm{\&Sigma;}}_{i+1}^n{x}_{\mathrm{ij}})(t_{i+1}-t_i)+1/{2v}_j(t_{i+1}^2-t_i^2))---(2-3)$

(2) at t ' sometime _i∈ [t _i, t _i+1) time, the j kind emergency resources of accident region A is exhausted,

Q _j(t _i)-v _j(t′ _i-t ₁)=0，(i=1，2，…，n，j=1，2，…m) （2-4）

According to formula (2-1) and formula (2-4), known

$\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_{\mathrm{ij}}-v_j(t_i-t_1)-v_j(t_i^{\&prime;}-t_1)=0$

Can draw t ' _ivalue,

$t_i^{\&prime;}=\frac{1}{v_j}{\mathrm{\&Sigma;}}_{i=1}^n{x}_{\mathrm{ij}}+t_1---(2-5)$

Therefore,

$\begin{array}{c}{\mathrm{Loss}}_j=U_j{C}_{i+1,j}+{\&Integral;}_i^{i+1}{v}_j\mathrm{tdt}=\frac{1}{2}{v}_j{U}_j{C}_{i+1}(t_{i+1}^2-t_i^{\&prime;2})\\ =\frac{1}{2}{v}_j{U}_j{C}_{i+1},j(t_{i+1}^2-{(\frac{1}{v_j}{\mathrm{\&Sigma;}}_{i=1}^n{x}_{\mathrm{ij}}+t_1)}^2);\end{array}---(2-6)$

(3) at moment t _iand t _i+1, Q _j(t _i) >0, (i=1,2 ..., n)., mean that causing damage because of the shortage of j kind emergency resources does not appear in accident region A, i.e. Loss _j=0, (j=1,2 ..., m, i=1,2 ..., n).

From the demand of emergency management and rescue and scheduling of resource, set up two evaluation objectives: (1) various emergency resources total transport costs herein; (2), because emergency resources can not be supplied to accident disaster area in time, institute results in greater loss and serious consequence.

According to the character of accident and urgency level, construct herein shown in step S200 can flexible evaluation weight minimize cost and loss model.

$\begin{array}{c}\min F=\mathrm{\&alpha;}{\mathrm{\&Sigma;}}_{j=1}^m{\mathrm{\&Sigma;}}_{i=1}^n{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\&beta;}{\mathrm{\&Sigma;}}_{j=1}^m{\mathrm{Loss}}_j=\\ \left\{\begin{array}{c}\mathrm{\&alpha;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{C}_{\mathrm{i\; j}}{x}_{\mathrm{ij}}+\mathrm{\&beta;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}(U_j{C}_{i+1,j}(v_j(t_i-t_1)-\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_{\mathrm{ij}})(t_{i+1}-t_i)+1/{2v}_j(t_{i+1}^2-t_i^2)),\\ \mathrm{\&alpha;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\&beta;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\left(\frac{1}{2}{v}_j{U}_j{C}_{i+1,j}(t_{i+1}^2-{(\frac{1}{v_j}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_{\mathrm{ij}}+t_1)}^2)\right),\\ \mathrm{\&alpha;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}},\end{array}\right.\end{array}---(2-7)$

And meet

It should be noted that:

1) the weight adjusting knob α in simulated target function and β are a positive number, and itself and be 1, can pass through these two weight adjusting knobs, with adaptive surface to the cost under emergency circumstances of different nature and loss assessment, especially in face of great especially accident, save disaster area people life property loss and ensure that disaster area common people's daily life need to be primary liability, β value can be tuned up as far as possible.

2) other constraint conditions of model

A) emergency resources that each feed point transports to accident disaster area can not exceed its stored number;

B) in whole rescue process, a certain emergency resources stored number summation of each emergency resources feed point should be greater than such emergency resources quantity consuming in whole emergency management and rescue process;

C) in whole rescue process, a certain emergency resources stored number summation of each emergency resources feed point should be greater than such emergency resources quantity that is transported to accident disaster area in whole emergency management and rescue process;

D) each emergency resources feed point increases progressively to accident disaster area haulage time.

S300, carry out selection operation, interlace operation and the mutation operation of emergency resources individuality, until meet end condition.

In view of the deficiency that traditional roulette selects operator to exist, technical solution of the present invention is further optimized the selection step of emergent scheduling of resource process, shown in Figure 3, mainly comprises:

D1, the least disadvantage value of all emergency resources individualities is sorted according to size, the difference of preferably loss value and differential loss mistake value is divided into M hierarchical region, loss is worth to best individuality and directly inserts progeny population, remaining individuality is dispensed to corresponding hierarchical region according to least disadvantage value separately;

D2, calculate the average minimum loss value A1 of each hierarchical region, described A1 is that the least disadvantage value sum of each individuality in current hierarchical region is divided by the individual amount of this grade district inclusion;

D3, carry out for the first time roulette and select operation, the average minimum loss value A1 that the selected probability B1 of each hierarchical region is current hierarchical region is divided by the average fitness value sum of all hierarchical regions;

D4, carry out for the second time roulette and select operation, calculate the selected probability B2 of each individuality in each hierarchical region, the minimum loss value that described B2 is this individuality is divided by the fitness sum of all individualities of current hierarchical region;

The selected probability B3 of each individuality in D5, calculating population S, B3 equals B1 and is multiplied by B2.

Wherein, described the least disadvantage value of all individualities is sorted and comprises according to order from small to large and arranging and order is from big to small arranged according to size.

Visible, divide according to the capable hierarchical region of individual least disadvantage, set up the average fitness value of hierarchical region.In the time that selected population is individual, first plan according to the average least disadvantage value roulette of hierarchical region, determine to choose the quantity of candidate's individuality from each hierarchical region, then in same hierarchical region, carrying out roulette selects individual again, on the resource scheduling that solves multi-peak, can set up adaptation mechanism by the method, automatically suppress population similar individuals too concentrated, improve population at individual diversity, select the better Function Solution of roulette selection algorithm thereby obtain than traditional elite.

Further, the interlace operation of carrying out emergency resources individuality described in comprises:

A point of crossing j of random selection, individual the parent of matrix coder Parent1 and Parent2 are divided into respectively to two parts, Parent1 is cut apart to the part that obtains and Parent2 and cut apart the corresponding part obtaining and carry out coordinated transposition, thereby obtain two new offspring individuals.

Shown in Fig. 4 (1), the individual Parent1 of two parents and Parent2 carry out matrix interlace operation: select at random a point of crossing j, individual parent Parent1 and Parent2 are divided into two parts separately, shown in Fig. 4 (2); The part4 coordinated transposition of the part1 of Parent1 and Parent2 produces two new offspring individuals, referring to Fig. 4 (3).

Simultaneously, technical solution of the present invention can utilize y-bend space cut tree to set up emergency resources scheduling scheme, whole parameter space is defined as to BSP tree root space, BSP sets these four information of search volume, node switch and pointer group that each node data structure comprises individual chromosome information, representative, its pointer group is for associated father node and two of left and right child node, node switch represents that whether this node is in state of atom, and whether its all dimensions search volume can be cut apart again.

Suppose S _m(i) be i chromosome individuality in contemporary population S, D is S _m(i) total dimension (genes of individuals quantity), R is gene value resolution (gene possibility value number), R ^dfor the size of whole search volume, the middle population at individual that genetic manipulation produces, by traversal BSP tree, is inserted in BSP tree, and in needs, completes mutation operation, and its step expects to equal O (logR ^d), along with the population that each genetic manipulation is produced constantly adds in BSP tree, the scale of BSP tree can constantly increase, and when the node of BSP tree has been covered with whole search volume, should stop the operation of algorithm.

Further, for correcting the individuality that repeats that the selection operator of traditional y-bend space cut tree and crossover operator effect produce, technical solution of the present invention is also optimized the mutation process of emergency resources individuality, realize the driving of variation certainly of carrying out Local Search, field search and cross-domain search in parameter space, change to a certain extent the characteristic of traditional genetic algorithm random search.

Therefore, the scheduling of the emergency resources towards complicated supply model that the embodiment of the present invention provides, take, by matrix-style, complicated multi-to-multi scheduling of resource is carried out to individuality coding, and make emergency resources according to the demand of relevant emergency resources kind and quantity in accident region and allot strategy, select to participate in the feed point of emergency resources rescue, loss is dropped to minimum, the method is applicable to the emergency resources of many emergency resources deposit point and diversified resource provision pattern under complicated deposit system and deposit network topology dispatches as far as possible.The black box processing factory that is simultaneously population at individual by design BSP tree, the middle population at individual producing after the selection operator of traditional algorithm and crossover operator effect is carried out to traversal search, sequence and newly-increased tree node, the individuality having repeated in evolution in contemporary population is carried out to local, neighborhood or cross-domain driving search variation according to the technical program and become a new individuality, realize with the less function calculation times of less convergence algebraic sum and obtain the emergency resources scheduling scheme with less cost and loss.

One of ordinary skill in the art will appreciate that all or part of step in the various flow processs of above-described embodiment is can carry out the hardware that instruction is relevant by program to complete, this program can be stored in a computer-readable recording medium, storage medium can comprise: ROM (read-only memory) (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), disk or CD etc.

, in the above-described embodiments, the description of each embodiment is all emphasized particularly on different fields meanwhile, in certain embodiment, there is no the part of detailed description, can be referring to the associated description of other embodiment.

A kind of emergency resources dispatching method towards complicated the supply model above embodiment of the present invention being provided is described in detail, applied specific case herein mutual principle of the present invention and embodiment are set forth, the explanation of above embodiment is just for helping to understand method of the present invention and core concept thereof; , for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention meanwhile.

Claims (10)

1. towards an emergency resources dispatching method for complicated supply model, it is characterized in that, described method comprises:

Initialization population: the emergency resources individuality in population S is carried out to matrix coder,

$S=\left[\begin{array}{cccccc}{x}_{11}& x_{12}& ...& x_{1j}& ...& x_{1m}\\ x_{21}& x_{22}& ...& x_{1j}& ...& x_{2m}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{i1}& x_{i2}& ...& x_{\mathrm{ij}}& ...& x_{\mathrm{im}}\\ .& .& & .& & .\\ .& .& ...& .& & .\\ .& .& & .& & .\\ x_{n1}& x_{n2}& ...& x_{\mathrm{nj}}& ...& x_{\mathrm{nm}}\end{array}\right]$

Wherein, n represents that total n emergency resources feed point participates in this emergency resources scheduling, and m represents that total m kind emergency resources need be dispatched to disaster area, 1≤i≤n, 1≤j≤m, x _ijrepresent to dispatch the quantity of j kind emergency resources to disaster area from i emergency resources feed point;

Calculate the loss value of each individuality in population according to default least disadvantage function,, wherein said least disadvantage refers to the least disadvantage min F causing due to the j kind emergency resources lacking in population S,

$\begin{array}{c}\min F=\mathrm{\&alpha;}{\mathrm{\&Sigma;}}_{j=1}^m{\mathrm{\&Sigma;}}_{i=1}^n{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\&beta;}{\mathrm{\&Sigma;}}_{j=1}^m{\mathrm{Loss}}_j=\\ \left\{\begin{array}{c}\mathrm{\&alpha;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{C}_{\mathrm{i\; j}}{x}_{\mathrm{ij}}+\mathrm{\&beta;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}(U_j{C}_{i+1,j}(v_j(t_i-t_1)-\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_{\mathrm{ij}})(t_{i+1}-t_i)+1/{2v}_j(t_{i+1}^2-t_i^2)),\\ \mathrm{\&alpha;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}}+\mathrm{\&beta;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\left(\frac{1}{2}{v}_j{U}_j{C}_{i+1,j}(t_{i+1}^2-{(\frac{1}{v_j}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_{\mathrm{ij}}+t_1)}^2)\right),\\ \mathrm{\&alpha;}\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{C}_{\mathrm{ij}}{x}_{\mathrm{ij}},\end{array}\right.\end{array}$

And meet

Wherein, v _jrepresent that emergency management and rescue start the spending rate of rear j kind emergency resources, U _jrepresent to lack in each unit interval the loss that the j kind emergency resources of a unit causes, C _ijrepresent that the j kind emergency resources of a unit is from i the emergency resources feed point transportation cost required to disaster area, α and β represent weight adjusting knob, and are positive number;

Carry out selection operation, interlace operation and the mutation operation of emergency resources individuality, until meet end condition.

2. method according to claim 1, it is characterized in that, the default least disadvantage function of described basis calculates the loss value of each individuality in population, and wherein said least disadvantage refers to that the least disadvantage min F causing due to the j kind emergency resources lacking in population S specifically comprises:

If at t _iin the moment, the j kind emergency resources in disaster area has been exhausted, the loss causing in default of j kind emergency resources

$\begin{array}{c}{\mathrm{Loss}}_j=-U_j{C}_{i+1,j}{\&Integral;}_i^{i+1}[Q_j\left(t_i\right)-v_{j}t]\mathrm{dt}\\ =-U_j{C}_{i+1,j}[Q_j\left(t_i\right)(t_{i+1}-t_i)-1/{2v}_j(t_{i+1}^2-t_i^2)\end{array}$

Wherein, Q _j(t _i) be at t _ithe j kind emergency resources volume residual in moment disaster area, $Q_j\left(t_i\right)={\mathrm{\&Sigma;}}_{i=1}^n{x}_{\mathrm{ij}}-$ $v_j(t_i-t_1);$

If at t _iin the ˊ moment, the j kind emergency resources in disaster area is exhausted, wherein t ' _i∈ [t _i, t _i+1), Q _j(t _i)-v _j(t ' _i-t ₁)=0, (i=1,2 ..., n, j=1,2 ... m), due to $Q_j\left(t_i\right)={\mathrm{\&Sigma;}}_{i=1}^n{x}_{\mathrm{ij}}-$ $v_j(t_i-t_1),$ So $t_i^{\&prime;}=\frac{1}{v_j}{\mathrm{\&Sigma;}}_{i=1}^n{x}_{\mathrm{ij}}+t_1,$ Thereby

$\begin{array}{c}{\mathrm{Loss}}_j=U_j{C}_{i+1,j}+{\&Integral;}_i^{i+1}{v}_j\mathrm{tdt}=\frac{1}{2}{v}_j{U}_j{C}_{i+1}(t_{i+1}^2-t_i^{\&prime;2})\\ =\frac{1}{2}{v}_j{U}_j{C}_{i+1},j(t_{i+1}^2-{(\frac{1}{v_j}{\mathrm{\&Sigma;}}_{i=1}^n{x}_{\mathrm{ij}}+t_1)}^2);\end{array}$

If at t _i+1in the moment, the j kind emergency resources in disaster area is not exhausted, Loss _j=0.

3. method according to claim 1, is characterized in that, described β is greater than 0.5.

4. method according to claim 1, is characterized in that, described in carry out emergency resources individuality selection operation comprise:

Least disadvantage value to all emergency resources individualities sorts according to size, the difference of preferably loss value and differential loss mistake value is divided into M hierarchical region, loss is worth to best individuality and directly inserts progeny population, remaining individuality is dispensed to corresponding hierarchical region according to least disadvantage value separately; ;

Calculate the average minimum loss value A1 of each hierarchical region, described A1 is that the least disadvantage value sum of each individuality in current hierarchical region is divided by the individual amount of this grade district inclusion;

Carry out roulette for the first time and select operation, the average minimum loss value A1 that the selected probability B1 of each hierarchical region is current hierarchical region is divided by the average fitness value sum of all hierarchical regions;

Carry out roulette for the second time and select operation, calculate the selected probability B2 of each individuality in each hierarchical region, the minimum loss value that described B2 is this individuality is divided by the fitness sum of all individualities of current hierarchical region;

Calculate the selected probability B3 of each individuality in population S, B3 equals B1 and is multiplied by B2.

5. method according to claim 1, is characterized in that, described in carry out emergency resources individuality interlace operation comprise:

A point of crossing j of random selection, individual the parent of matrix coder Parent1 and Parent2 are divided into respectively to two parts, Parent1 is cut apart to the part that obtains and Parent2 and cut apart the corresponding part obtaining and carry out coordinated transposition, thereby obtain two new offspring individuals.

6. method according to claim 1, is characterized in that, described in carry out emergency resources individuality selection operation comprise:

From the root node of y-bend space cut tree, according to first pre-conditioned definite x _ijbelong to left sibling space or right node space, and continue search downwards along the node direction of subspace, place, till searching leaf node;

If described x _ijdo not repeat with first front nodal point in the cut tree of y-bend space, directly insert y-bend space cut tree, as new leaf node; Wherein, if described x _ijfather node without left child node, described x _ijdirectly inherit his father's node searching subspace as left child node, if described x _ijthe existing left child node x of father node _ijˊ, according to the second pre-conditioned position adjustment of carrying out left child node and right child node;

If described x _ijwhen inserting y-bend space cut tree and having carried out subspace cutting operation, the left child node after inspection is cut apart and right child node search volume, whether in indivisible state, if so, arrange described x _ijposition is closed condition.

7. method according to claim 6, is characterized in that, described in carry out emergency resources individuality mutation operation comprise:

If inserting the individual x of new chromosome _rztime there is x _rzwith x _ijrepeat, wherein 1≤r≤n, 1≤z≤m, at x _ijthe search subspace Subspace(x shining upon _ij) in scope to x _rzcarry out mutation operation, or at Subspace(x _ij) neighborhood within the scope of to x _rzcarry out mutation operation, or be not subject to Subspace(x _ij) restriction of scope is to S(j) carry out mutation operation.

8. method according to claim 7, is characterized in that, is inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, at x _ijthe search subspace Subspace(x shining upon _ij) in scope to x _rzcarrying out mutation operation comprises:

Determine Subspace(x _ij) whether the position of the switch be open state, if so, works as x _ijleft child node or right child node be empty, select Subspace(x _ij) gene position of dimensional space maximum, x _rzat described Subspace(x _ij) genetic mutation is carried out in the corresponding gene position of selecting within the scope of dimensional space; If the x after variation _rzstill with x _ijidentical, stop x _rzcarry out again mutation operation.

9. method according to claim 7, is characterized in that, is inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, at Subspace(x _ij) neighborhood within the scope of to x _rzcarrying out mutation operation comprises:

Determine described x _ijthe search subspace Subspace(x shining upon _ij) whether the position of the switch be closed condition, if so, rollback to described x _ijfather node, and judge described x _ijbrotgher of node x _pqthe search subspace Subspace(x shining upon _pq) whether the position of the switch be open state, if so,

Scan the individual x of new chromosome _rzeach gene whether belong to Subspace(x _pq), by the gene not belonging at Subspace(x _pq) carry out random variation in corresponding dimensional space.

10. method according to claim 7, is characterized in that, is inserting the individual x of new chromosome if described _rztime there is x _rzwith x _ijrepeat, be not subject to Subspace(x _ij) restriction of scope is to x _rzcarrying out mutation operation comprises:

Determine described x _ijleft child node space and right child node space whether be closed condition, if so,

The individual x of new chromosome _rzgene random variation in its original dimensions spatial dimension be x _rz, from the root node search x of y-bend space cut tree _rzaffiliated node subspace.