CN105046363A - Gridding method for one-line diagram layout and optimization of zone electric distribution system - Google Patents

Abstract

The invention discloses a gridding method for one-line diagram layout and optimization of a zone electric distribution system. The method comprises the following steps of: gridding a layout space, forming a grid lattice of a node layout solution space and a line corridor space of lines, and limiting the node layout solution space in the grid lattice of nodes; describing each grid state by adopting a relevant enumeration variable; performing node layout, establishing a node layout model, and adopting a shortest Manhattan distance of the nodes as a target function for node layout and optimization; performing mapping and initialization, determining the position of a transformer substation in grids according to relative geographic information by utilizing hierarchical branch attributes of a power distribution line, and arranging branch contact lines of a distribution network by selecting a hierarchical layout algorithm; introducing a self-adaptive crossover probability, and introducing different crossover probabilities for different fitness values; and avoiding overlapping and crossing situations of the lines. The gridding method disclosed by the invention effectively assists in node layout and optimization of a one-line diagram and arrangement of the lines in the zone electric distribution system.

Description

The gridding method of a kind of region distribution system line chart layout and optimization

Technical field

The present invention relates to the gridding method of a kind of region distribution system line chart layout and optimization.

Background technology

Electrical single-line diagram automatic mapping technology is one of the important subject in graph visualization field, is also to realize the intelligentized a kind of common support technology of system software.Urban Medium Voltage Distribution Network network is owing to adopting the multiple ring-like modes of connection such as Single-ring network, dual-ring network and the multi-joint network of many segmentations, and the degree of coupling of node increases, and the complexity of network structure also increases thereupon, proposes a new difficult problem therefore also to line chart automatic mapping.In existing pattern layout algorithm, hierarchy type placement algorithm ^[1]be only applicable to radially wait the relatively simple network of topological structure, for ring network then body limit its limitation; Gridding method ^[2]tend to the neat, attractive in appearance of layout graph effect, but huge for catenet calculated amount, be difficult to realize fast search; Continuous print power guidance algorithm ^[3]simply be easy to realize, but then easily produce uneven length of side distribution for contacting complicated network between node, affect the aesthetic property of figure.Above-mentioned algorithm is all difficult to the automatic layout being applied to ring-like distribution system.

Summary of the invention

The present invention is in order to solve the problem, propose the gridding method of a kind of region distribution system line chart layout and optimization, this method relies on the advantage of grid layout in the visual application of complex network, studies the arrangement problem of the great deal of nodes of region distribution system line chart based on discrete grid block technology and the line relation between them.

To achieve these goals, the present invention adopts following technical scheme:

A gridding method for region distribution system line chart layout and optimization, comprises the following steps:

(1) set up the Optimized model of node layout: zoning distribution network, build effective grid collection, be disposed in order branch line node;

(2) genetic algorithm is passed through, the optimum individual in chess game optimization model is carried out in overall parallel search mode, first time genetic algorithm to obtain between website after line node layout, the branch node determined position is as the constraint of genetic algorithm next time, and iteration asks for the layout of residue circuit again;

(3) carry out mapping and initialization, with the whole story two website lines for diagonal line, obtaining its smooth vertical and horizontal rectangular edges is path, extends, and produces path collection;

(4) adopt optimum maintaining strategy evolution Model, the evolution of every generation is retained current optimum individual and does not participate in genetic operation, and directly its stable state is copied to colony of future generation;

(5) determine port position, with line route sound out, juxtaposition judges, the placement strategy of adjustment carries out internodal line, avoid the overlap of cabling, crossing instances and by trellis state numerical examination, the coordinate of all nodes connected up.

The concrete grammar of described step (1) is: defining a regional distribution network network is a tlv triple G=(V, S, l, n), and wherein V is the set of node; S is transformer station's set, and l connects the branch line set between any Liang Ge transformer station, and n is regional power grid transformer station number, makes l _pq: S ₅→ S ₅for connecting transformer station S _pwith S _qa branch line, wherein branch line l _pqcomprise set of node { V _j, V _j+1... V _i, number is C _nodes(l _pq), for any branch line l _pq, being located at respective paths painting canvas connecting its first and last transformer station is L _pq, shared effective grid collection is { g ₁, g ₂... g _s, number is C _grids(L _pq), provide the computing formula of line chart node layout objective function:

$f=min\underset{i=1}{\overset{n}{\Σ}}\underset{j=1}{\overset{n}{\Σ}}|C_{grids}\left(L_{ij}\right)-C_{nodes}\left(l_{ij}\right)|$

s.t.S _Xk＝C _kx

S _Yk＝C _ky(1)

From L in formula (1) _m={ g ₁, g ₂... g _schoose C _nodes(l _i) individual effective grid sequentially arranges branch line node, can obtain each node x _k, y _kfor coordinate; S _xk, S _ykbe respectively x corresponding to a kth plant stand, y-axis coordinate figure; C _kx, C _kyfor the coordinate constant of the relatively geographical position calculation gained according to transformer station.

In described step (2), genetic algorithm is a kind of simulation biological evolution basic process, the optimum individual in chess game optimization colony is carried out in overall parallel search mode, try to achieve the method for the optimum solution met the demands, according to distribution network line feature, except directly connecting the circuit of two websites, also there is some branched lines of drawing in the middle of circuit, therefore, according to above-mentioned thinking, adopt the optimization that one time genetic algorithm iteration cannot complete whole system, first time genetic algorithm to obtain between website after line node layout, the branch node determined position is as the constraint of genetic algorithm next time, again iteration asks for the layout of residue circuit.

In described step (3), gene code is with collection L in path between website _pqfor population gene, C={L ₁, L ₂... L _m, i=1,2 ..., k, k are chromosome length, with the chromosome of concrete path for place gene, that is: and L _pq={ g ₁, g ₂... g _s, g _j=(x, y), j=1,2 ..., s.

In described step (3), the concrete production method that initial path integrates is: with the whole story two website lines as diagonal line, obtaining its smooth vertical and horizontal rectangular edges is path, other routing with first rectangular edges for bounding box other rectangular edges outward extending, produce one group of path collection, need to carry out trellis state checking when generation circuit and obtain its validity.

In described step (4), the individuality that in current group, fitness is best is destroyed for preventing the randomness of genetic manipulation, affect optimal speed, selection opertor adopts optimum maintaining strategy evolution Model, namely the evolution of every generation retains the genetic operation that current optimum individual does not participate in intersection, variation, and directly its stable state is copied in colony of future generation.

In described step (4), crossover operator: reorganization operation of intersecting is concentrated by selecting paths two paths to carry out, exchanges the new initial path point sequence of generation two, in order to ensure that path can in a rectangle frame,, with a rectangular edges for intersect unit, after intersecting, empty portions in path need be extended, make path keep sealing range;

Mutation operator makes traversal path grid can further close to a kind of mode of line node sum, adopt multiple spot gene position variation mode, be specially ask in neighborhood not by the effective grid that pel covers, to make in path corresponding grid sudden change extremely in effective blank grid.

In described step (5), node represents with a horizontal line in the drawings, and the first and last section of the connecting line between node a and node b is called outlet port, and outlet is orthogonal with node in outlet port to connect.

In described step (5), concrete grammar is:

Regularly wiring path is arranged in storehouse, then check whether to exist and intersect and overlapping situation, if have, then adjust path, until meet cabling requirement, this process is exploration process, and basis for estimation is as follows: in grid shared by the path L of known connection scene 2 line cap, if exist 0 taken by other cablings grid time for without juxtaposition; Be greater than if exist 0 discrete when taking grid for intersecting; Deposit and to be more than or equal to when 2 continuous print have taken grid for overlapping, corresponding trellis state Boolean variable m_nState value is set according to judged result, supposes that the numeric representation of the i-th row j row trellis state in arrangement space is φ (i, j), then have:

In formula, ε is the weights introducing crossover node, gets ε=10; The then wiring path state and be from node a to node b:

$S=\underset{i=x}{\overset{x\∈L_x}{\Σ}}\underset{j=y}{\overset{y\∈L_y}{\Σ}}\mathrm{\φ}(i,j)---\left(3\right)$

L is the cabling in node a to b path, L _xby path L the row of process, L _yby path L the row of process.

In described step (5), the exploration of path L, local optimal searching and method of adjustment are make l be straight line minimum with two node outgoing port place linear correlations among all broken lines of path L, state and minimum route searching flow process as follows;

Step1: make l be with (x ₁, y ₁) and (x ₂, y ₂) be the straight-line segment of end points, wherein calculate $S=\underset{i=x}{\overset{x\∈L_x}{\Σ}}\underset{j=y}{\overset{y\∈L_y}{\Σ}}\mathrm{\φ}(i,j),$ Turn to step4;

Step2: make (x ₁, y ₁) and (x ₂, y ₂) for the straight line of end points is toward a parallel direction left side/top translation 1 cell overlapped, calculate $S=\underset{i=x}{\overset{x\∈L_x}{\Σ}}\underset{j=y}{\overset{y\∈L_y}{\Σ}}\mathrm{\φ}(i,j),$ Turn to step4;

Step3: make (x ₁, y ₁) and (x ₂, y ₂) for the straight line of end points is toward right/following translation 1 cell of the horizontal direction overlapped, calculate $S=\underset{i=x}{\overset{x\∈L_x}{\Σ}}\underset{j=y}{\overset{y\∈L_y}{\Σ}}\mathrm{\φ}(i,j),$ Turn to step4;

Step4: if S ≠+∞, turn to step6; If S=+ is ∞, turn to step2;

Step5: if S ≠+∞, turn to step6; If S=+ is ∞, turn to step3;

Step6: terminate.

Beneficial effect of the present invention is:

(1) node layout that the gridding method proposed facilitates region distribution system line chart effectively optimizes the layout with circuit cabling;

(2) in the node layout's optimized algorithm adopted, by the crossover operator in improved adaptive GA-IAGA, enhance ability of searching optimum, improve algorithm convergence efficiency;

(3) quantizing by trellis state, makes cabling juxtaposition problem determination more quick, simple, improves positioning efficiency;

(4) can make to be uniformly distributed in node and figure, cabling is attractive in appearance clear, and counting yield and graphical effect can meet Practical requirement.

Accompanying drawing explanation

Fig. 1 is Load flow calculation process flow diagram;

Fig. 2 is two kinds of crossover operator schematic diagram;

Fig. 3 is gained path schematic diagram after intersecting;

Fig. 4 is path individual variation process schematic;

Fig. 5 be node i and j level time port direction schematic diagram;

Fig. 6 be node i vertical with j time port direction schematic diagram;

Fig. 7 is the port direction schematic diagram that node i and j are in diagonal angle.

Embodiment:

Below in conjunction with accompanying drawing and embodiment, the invention will be further described.

The application of 1 genetic algorithm in node layout

The universal model of 1.1 node layout's problems

For making the distribution of node geometry have good corresponding relation with network connectivity logic, first arrangement space is separated into the anyhow neat grid that the capable v of u arranges, each node occupies a grid, adopts the state of a Boolean variable indicia grid simultaneously.On the other hand, see that figure is accustomed in order to what meet operations staff, Ying Shi transformer station position and geographical relative position broadly similar, be converted into coordinate constant by plant stand geography information in network herein, is placed in corresponding grid, as the constraint of optimization problem.

After plant stand position is fixing, line arrangement problem between plant stand can regard as path planning problem, general thought circuit is seen as the area routing that first and last point determines, node be considered to connect up on a series of path point, by supposing in advance a series of paths collection, according to interstitial content, once operation is restrained to initial path point sequence, finally converge to one and to arrange path as the node of circuit with the minimum path of node phase margin.Due to the mutual independence in each path, every bar circuit can find respective phase margin minimal path independently, and adopts a kind of parallel network structure to realize.

In order to realize above-mentioned target, first need the Optimized model setting up node layout.Conveniently discuss, provide following 2 definition about figure related notion herein.

Defining 1 one regional distribution network networks is a tlv triple G=(V, S, l, n), and wherein V is the set of node; S is transformer station's set, and l connects the branch line set between any Liang Ge transformer station, and n is regional power grid transformer station number.Make l _pq: S ₅→ S ₅for connecting transformer station S _pwith S _qa branch line, wherein branch line l _pqcomprise set of node { V _j, V _j+1... V _i, number is C _nodes(l _pq).

Definition 2 is for any branch line l _pq, being located at respective paths painting canvas connecting its first and last transformer station is L _pq, shared effective grid collection is { g ₁, g ₂... g _s, number is C _grids(L _pq).

According to above definition and about marking, we provide the computing formula of line chart node layout objective function:

$f=min\underset{i=1}{\overset{n}{\Σ}}\underset{j=1}{\overset{n}{\Σ}}|C_{grids}\left(L_{ij}\right)-C_{nodes}\left(l_{ij}\right)|$

s.t.S _Xk＝C _kx

S _Yk＝C _ky(1)

From L in formula (1) _m={ g ₁, g ₂... g _schoose C _nodes(l _i) individual effective grid sequentially arranges branch line node, can obtain each node x _k, y _kfor coordinate; C _kx, C _kyfor the coordinate constant of the relatively geographical position calculation gained according to transformer station.L _mfor path, g _j=(x, y) refers to coordinate figure.

1.2 genetic algorithms ask for path

Genetic algorithm is a kind of simulation biological evolution basic process, carrys out the optimum individual in chess game optimization colony, try to achieve the method for the optimum solution met the demands in overall parallel search mode.According to distribution network line feature, except directly connecting the circuit of two websites, also there is some branched lines of drawing in the middle of circuit.Therefore, according to above-mentioned thinking, adopt the optimization that one time genetic algorithm iteration cannot complete whole system, we can to obtain between website after line node layout in first time genetic algorithm, the branch node determined position is as the constraint of genetic algorithm next time, and iteration asks for the layout of residue circuit again.Wherein the general process followed of genetic algorithm as shown in Figure 1.

1.2.1 the mapping of gene and initialization

Gene code is with collection L in path between website _pqfor population gene, C={L ₁, L ₂... L _m, i=1,2 ..., k, k are chromosome length, with the chromosome of concrete path for place gene, that is: and L _pq={ g ₁, g ₂... g _s, g _j=(x, y), j=1,2 ..., s.

The generation of initial path collection.According to algorithm thinking introduced above, the website that any two logics are connected all needs to produce a series of path sequence, in order to make the circuit logic of layout clear, initial path integrates follows such thinking: with the whole story two website lines as diagonal line, obtaining its smooth vertical and horizontal rectangular edges is path, other path can be selected with first rectangular edges, for bounding box other rectangular edges outward extending, thus, to produce one group of path collection.It should be noted that in path planning problem as herein described, the generation that repeats avoiding path is very important, because in path production process corresponding to different circuit, likely occur the situation converging to same path, thus cause circuit arranged superposed.In order to avoid this kind of situation, need to carry out trellis state checking when generation circuit and obtain its validity.

1.2.2 select, intersect and mutation operator

Selecting, intersecting and make a variation is operator important in genetic algorithm.The individuality that in current group, fitness is best is destroyed for preventing the randomness of genetic manipulation, affect optimal speed, selection opertor adopts optimum maintaining strategy evolution Model herein, namely the evolution of every generation retains current optimum individual and does not participate in the genetic operation such as intersection, variation, and directly its stable state is copied in colony of future generation.The design of all the other crossover and mutation operators is as follows.

Crossover operator: reorganization operation of intersecting is concentrated by selecting paths two paths to carry out part to exchange the new initial path point sequence of generation two, in order to ensure that path can in a rectangle frame, herein with a rectangular edges for intersecting unit, after intersecting, empty portions in path need be extended, make path keep sealing range.

Mutation operator: mutation operator makes traversal path grid can further close to a kind of mode of line node sum, adopt multiple spot gene position variation mode herein, be specially ask in neighborhood not by the effective grid that pel covers, to make in path corresponding grid sudden change extremely in effective blank grid.

Wherein intersection and mutation probability adopt permanent amount p respectively _c, p _m.

2 wiring process

Complete after node layout optimizes, need carry out arrangement nodes line and carry out cabling in circuit corridor space, and by trellis state numerical examination and overlap, the crossing instances of avoiding cabling as far as possible, make figure entirety clear attractive in appearance.

Whole wiring process can be divided into that port position is determined, route searching two steps, for the line between node a and node b, wiring process is described.

The determination of 2.1 port position

Node represents with a horizontal line in the drawings, and the first and last section of the connecting line between node a and node b is called outlet port, and outlet is orthogonal with node in outlet port to connect.The direction of port is divided into 2 kinds of situations: 1) two Nodes outlet port direction are identical; 2) two Nodes outlet port direction are contrary.Fig. 5, Fig. 6, Fig. 7 show that node relative position is several outlet port direction types of horizontal line direction, perpendicular line direction and diagonal respectively.

2.2 internodal lines

Between node, line adopts the placement strategy that line route is soundd out, juxtaposition judges, adjusts.

Different according to node relative position, set up the rule base that wiring path is selected, wherein in Fig. 5,6,7, cabling numeral order is the priority of rule base interior joint relative position routing.According to node relative position rule searching storehouse, then can set up the path that connects first and last outlet port.

Whether first regularly wiring path is arranged in storehouse, then check to exist to intersect and overlapping situation, if having, then adjust path, until meet cabling requirement, this process is exploration process.Basis for estimation is as follows: in grid shared by the path L of known connection scene 2 line cap, if exist 0 taken by other cablings grid time for without juxtaposition; Be greater than if exist 0 discrete when taking grid for intersecting; Deposit and be more than or equal to when 2 continuous print have taken grid for overlapping.According to judged result, we can arrange corresponding trellis state Boolean variable m_nState value.The numeric representation supposing the i-th row j row trellis state in arrangement space is φ (i, j), then have:

In formula, ε is the weights introducing crossover node, gets ε=10; The then wiring path state and be from node a to node b:

$S=\underset{i=x}{\overset{x\∈L_x}{\Σ}}\underset{j=y}{\overset{y\∈L_y}{\Σ}}\mathrm{\φ}(i,j)---\left(3\right)$

L is the cabling in node a to b path, L _xby path L the row of process, L _yby path L the row of process.

The exploration of path L, local optimal searching and method of adjustment are make l be straight line minimum with two node outgoing port place linear correlations among all broken lines of path L, state and minimum route searching flow process as follows.

Step1: make l be with (x ₁, y ₁) and (x ₂, y ₂) be the straight-line segment of end points, wherein calculating formula (3), makes S ₀=S, turns to step4;

Step2: make (x ₁, y ₁) and (x ₂, y ₂) for the straight line of end points is toward a parallel direction left side/top translation 1 cell overlapped, turn to step1;

Step3: make (x ₁, y ₁) and (x ₂, y ₂) for the straight line of end points is toward right/following translation 1 cell of the horizontal direction overlapped, turn to step1;

Step4: if S ₀≠+∞, turns to step6; If S ₀=+∞, turns to step2;

Step5: if S ≠+∞, turn to step6; If S=+ is ∞, turn to step3.

Step6: terminate.

The standardization support technology of 3 graphics systems

For realizing sharing and interoperability of system figure, this graphics system, with reference to the graphical interaction scheme of IEC61970, adopts respectively model description and file layout and follows the foundation of the standardized way such as common information model (CIM) and easily extensible vector graphics (SVG).Wires and Topology bag in distribution network topological relation application CIM file describes, and wherein system connectivity model is described through ConductingEquipment-Terminal-ConnectivityNode three to set up.Secondly, also need to set up the public pel bag based on SVG, comprising plant stand is rectangle frame, and node is strigula, and overhead transmission line is fine line, and power cable line is dotted line.

Follow model and the icon saving format of CIM_SVG, and the above-mentioned grid automaticaldeveloping drawings algorithm based on genetic algorithm, as the three large technology essential factors building figure system constructing, when system and other application programs are carried out mutual, only standardized graphics file simply need be imported and derive, the graphic file of the standardization figure meeting electric power enterprise particular demands can be generated.

4 examples

Carry out to power distribution system network the test that line chart generates automatically according to said method, selected zone network is containing 3 transformer stations, totally 7 feeder lines, and more than 30 node, plants group mean adaptive value and be increased to 89% from 50% in 2s.From pattern layout's result, generate transformer station in figure and keep geographical relative position, line construction is clear, Node distribution is well-balanced, meets Practical requirement.

By reference to the accompanying drawings the specific embodiment of the present invention is described although above-mentioned; but not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of technical scheme of the present invention, those skilled in the art do not need to pay various amendment or distortion that creative work can make still within protection scope of the present invention.

Claims (10)

1. a gridding method for region distribution system line chart layout and optimization, is characterized in that: comprise the following steps:

(1) set up the Optimized model of node layout: zoning distribution network, build effective grid collection, be disposed in order branch line node;

(2) genetic algorithm is passed through, the optimum individual in chess game optimization model is carried out in overall parallel search mode, first time genetic algorithm to obtain between website after line node layout, the branch node determined position is as the constraint of genetic algorithm next time, and iteration asks for the layout of residue circuit again;

(3) carry out mapping and initialization, with the whole story two website lines for diagonal line, obtaining its smooth vertical and horizontal rectangular edges is path, extends, and produces path collection;

(4) adopt optimum maintaining strategy evolution Model, the evolution of every generation is retained current optimum individual and does not participate in genetic operation, and directly its stable state is copied to colony of future generation;

(5) determine port position, with line route sound out, juxtaposition judges, the placement strategy of adjustment carries out internodal line, avoid the overlap of cabling, crossing instances and by trellis state numerical examination, the coordinate of all nodes connected up.

2. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, it is characterized in that: the concrete grammar of described step (1) is: defining a regional distribution network network is a tlv triple G=(V, S, l, n), wherein V is the set of node; S is transformer station's set, and l connects the branch line set between any Liang Ge transformer station, and n is regional power grid transformer station number, makes l _pq: S ₅→ S ₅for connecting transformer station S _pwith S _qa branch line, wherein branch line l _pqcomprise set of node { V _j, V _j+1... V _i, number is C _nodes(l _pq), for any branch line l _pq, being located at respective paths painting canvas connecting its first and last transformer station is L _pq, shared effective grid collection is { g ₁, g ₂... g _s, number is C _grids(L _pq), provide the computing formula of line chart node layout objective function:

$f=min\underset{i=1}{\overset{n}{\Σ}}\underset{j=1}{\overset{n}{\Σ}}|C_{grids}\left(L_{ij}\right)-C_{nodes}\left(l_{ij}\right)|$

s.t.S _Xk＝C _kx

S _Yk＝C _ky(1)

From L in formula (1) _m={ g ₁, g ₂... g _schoose C _nodes(l _i) individual effective grid sequentially arranges branch line node, can obtain each node x _k, y _kfor coordinate; S _xk, S _ykbe respectively x corresponding to a kth plant stand, y-axis coordinate figure; C _kx, C _kyfor the coordinate constant of the relatively geographical position calculation gained according to transformer station.

3. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, it is characterized in that: in described step (2), genetic algorithm is a kind of simulation biological evolution basic process, the optimum individual in chess game optimization colony is carried out in overall parallel search mode, try to achieve the method for the optimum solution met the demands, according to distribution network line feature, except directly connecting the circuit of two websites, also there is some branched lines of drawing in the middle of circuit, therefore, according to above-mentioned thinking, adopt the optimization that one time genetic algorithm iteration cannot complete whole system, first time genetic algorithm to obtain between website after line node layout, the branch node determined position is as the constraint of genetic algorithm next time, again iteration asks for the layout of residue circuit.

4. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, is characterized in that: in described step (3), and gene code is with collection L in path between website _pqfor population gene, C={L ₁, L ₂... L _m, i=1,2 ..., k, k are chromosome length, with the chromosome of concrete path for place gene, that is: and L _pq={ g ₁, g ₂... g _s, g _j=(x, y), j=1,2 ..., s.

5. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, it is characterized in that: in described step (3), the concrete production method that initial path integrates is: with the whole story two website lines as diagonal line, obtaining its smooth vertical and horizontal rectangular edges is path, other routing with first rectangular edges for bounding box other rectangular edges outward extending, produce one group of path collection, need to carry out trellis state checking when generation circuit and obtain its validity.

6. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, it is characterized in that: in described step (4), the individuality that in current group, fitness is best is destroyed for preventing the randomness of genetic manipulation, affect optimal speed, selection opertor adopts optimum maintaining strategy evolution Model, namely the evolution of every generation retains the genetic operation that current optimum individual does not participate in intersection, variation, and directly its stable state is copied in colony of future generation.

7. the gridding method of a kind of region distribution system line chart layout as claimed in claim 6 and optimization, it is characterized in that: in described step (4), crossover operator: reorganization operation of intersecting is concentrated by selecting paths two paths to carry out, exchanges the new initial path point sequence of generation two, in order to ensure that path can in a rectangle frame,, with a rectangular edges for intersect unit, after intersecting, empty portions in path need be extended, make path keep sealing range;

Mutation operator makes traversal path grid can further close to a kind of mode of line node sum, adopt multiple spot gene position variation mode, be specially ask in neighborhood not by the effective grid that pel covers, to make in path corresponding grid sudden change extremely in effective blank grid.

8. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, it is characterized in that: in described step (5), node represents with a horizontal line in the drawings, the first and last section of the connecting line between node a and node b is called outlet port, and outlet is orthogonal with node in outlet port to connect.

9. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, is characterized in that: in described step (5), concrete grammar is:

Regularly wiring path is arranged in storehouse, then check whether to exist and intersect and overlapping situation, if have, then adjust path, until meet cabling requirement, this process is exploration process, and basis for estimation is as follows: in grid shared by the path L of known connection scene 2 line cap, if exist 0 taken by other cablings grid time for without juxtaposition; Be greater than if exist 0 discrete when taking grid for intersecting; Deposit and to be more than or equal to when 2 continuous print have taken grid for overlapping, corresponding trellis state Boolean variable m_nState value is set according to judged result, supposes that the numeric representation of the i-th row j row trellis state in arrangement space is then have:

In formula, ε is the weights introducing crossover node, gets ε=10; The then wiring path state and be from node a to node b:

$S=\underset{i=x}{\overset{x\∈L_x}{\Σ}}\underset{j=y}{\overset{y\∈L_y}{\Σ}}\mathrm{\φ}(i,j)---\left(3\right)$

L is the cabling in node a to b path, L _xby path L the row of process, L _yby path L the row of process.

10. the gridding method of a kind of region distribution system line chart layout as claimed in claim 1 and optimization, it is characterized in that: in described step (5), the exploration of path L, local optimal searching and method of adjustment are, make l be straight line minimum with two node outgoing port place linear correlations among all broken lines of path L, state and minimum route searching flow process as follows;

Step1: make l be with (x ₁, y ₁) and (x ₂, y ₂) be the straight-line segment of end points, wherein calculate $S=\underset{i=x}{\overset{x\∈L_s}{\mathrm{\Σ}}}\underset{j=y}{\overset{y\∈L_y}{\mathrm{\Σ}}}\mathrm{\φ}(i,j),$ Turn to step4;

Step2: make (x ₁, y ₁) and (x ₂, y ₂) for the straight line of end points is toward a parallel direction left side/top translation 1 cell overlapped, calculate turn to step4;

Step3: make (x ₁, y ₁) and (x ₂, y ₂) for the straight line of end points is toward right/following translation 1 cell of the horizontal direction overlapped, calculate turn to step4;

Step4: if S ≠+∞, turn to step6; If S=+ is ∞, turn to step2;

Step5: if S ≠+∞, turn to step6; If S=+ is ∞, turn to step3;

Step6: terminate.