CN102436604B - Multi-missile collaborative route calculation method based on multi-target evolution method - Google Patents

Abstract

The invention provides a multi-missile collaborative route calculation method based on a multi-target evolution method, which belongs to the technical field of task planning. The method specifically comprises the steps of: coding missile routes, defining missile mobility characteristics, modeling a planning area, generating route initial populations, evolving the route initial populations to generate new-generation route populations, evaluating the new-generation route populations to generate a rout set Q, evolving the route set Q among the populations to obtain a new-generation route set Q', evaluating the obtained new-generation route set Q', judging whether collaborative conditions are satisfied or not and the like. The method provided by the invention abandons the traditional route planning mode aiming at a single missile and can conduct collaborative planning to multiple missiles. By giving full consideration to the spatial conflict relationship and the attack arrival time relationship among the multiple missiles during planning, the realization of simultaneous set-time attacks to multiple enemy targets, saturation attacks to a certain enemy target and the like is facilitated and the attack efficiency is improved.

Description

Air route computing method worked in coordination with by a kind of many bullets based on multi-target evolution method

Technical field

The invention belongs to mission planning technical field, be specifically related to a kind of many bullets based on multi-target evolution method and work in coordination with air route computing method.

Background technology

Routeing is one of core of task grouping, its core content is the point selecting to meet a series of constraint condition between initial point and impact point, and under constraint condition, it is optimized, obtain one and optimize air route, say in a sense, make the optimization problem that specific aim and various restricted function match exactly.The object of guided missile routeing utilizes geography information and battlefield surroundings information, and under the prerequisite meeting various constraint condition, the flight route of planning guided missile, makes the specific evaluation index of guided missile reach optimum, thus improve the fighting efficiency of guided missile.

For in the routeing process of guided missile, need to understand and grasp the many-sided information such as geography information, position coordinates between ourselves and the enemy and motion conditions, the antiaircraft fire distribution of enemy, the performance of weapon such as planning region.These information are carried out routeing in conjunction with the constraint of guided missile self, and be a complicated multi-target non-linear optimization problem, its calculated amount is large, and computation process is very complicated.In addition, the antiaircraft technology of modern war is growing, make a good job of combat duty, carries out reliability strike, also needs to implement time attack of many ripples, saturation attack etc. to the same target with antiaircraft facility.In many ripples time are attacked, routeing must coordinate the attack time difference between each ripple time; In saturation attack, routeing must coordinate the attack time of each piece of guided missile setting.How to generate effective air route for each piece of guided missile, and the time that the air route voyage adjusting each piece of guided missile strikes target to coordinate it, be one of precondition of strike mission.

At present, conventional Route planner has Voronoi figure method, Grid Method, mathematic programming methods, Artificial Potential Field Method and genetic algorithm etc.

Its ultimate principle of Voronoi figure method is that environment space is divided into several regions, the border of a barrier is only comprised in each region, and to compare obstacles borders in other region all short for the distance of obstacles borders in environment space any point to one's respective area, a shortest path is searched out in the middle of the set between starting point to impact point be made up of zone boundary, even if the advantage of this paths is to produce site error, mobile robot also can not collision obstacle, relatively safe.Its shortcoming be the air route of planning out too close to barrier, and error is larger.

The main thought of Grid Method is that the environment space of aircraft is resolved into a series of grid cell with binary message, most use quaternary tree or Octatree technique.Wherein main division methods is: each grid cell have recorded environment space information, and have the local accumulated value of barrier higher, therefore environment space information can be quantified as the grid with certain resolution.By Optimizing Search strategy, aircraft will be avoided obstacle and complete routeing in the middle of these grids.Grid Method has consistance, standardization and simplicity in the expression of environment space, but does not consider the characteristic distributions of environment itself, depends on the requirement to precision, search has blindness, when circumstance complication, what search volume can be suitable is large, and efficiency of algorithm is very low.

Mathematic programming methods usually will be kept away barrier issue table and will be shown as a series of inequality constrain, and like this, path planning problem just can be expressed as the optimization problem being with Prescribed Properties.One large advantage of these class methods is exactly except Distance geometry obstacle, can also consider multiple other key elements relevant to path, as the security, enforceability etc. in path.Because this optimization problem is normally nonlinear, and with multiple inequality constrain, generally need solve with numerical approach.Mathematic programming methods is used for solution path and plans that general calculated amount is all very large, and is subject to the impact of local minimum, usually only for local paths planning.

The basic thought of Artificial Potential Field Method the motion of mobile robot in environment space is considered as the motion in a kind of virtual artificial stressed field.Impact point produces gravitation to robot, and barrier produces repulsion to it.Potential field is produced by gravitation and repulsion, under robot is subject to the effect of abstract power in potential field, can avoiding barrier.The method structure is simple, is easy to realize, and is widely applied in the active path planning under process circumstances not known information, but this method is easily absorbed in local optimum, produce of deadlock phenomenon, namely can not find path, easily shake before barrier between close barrier.

Genetic algorithm is based on the biological evolution theory such as genetic mechanism and natural selection, by the process of mathematics and computer simulation biological evolution.Its basic thought is: each path point in path planning is configured to the individuality existed in a coded form, and these individualities constitute a population.By setting up fitness function, carrying out selecting in the middle of population, the genetic manipulation such as crossover and mutation, through the evolution in some generations, to the last producing and meeting the desired filial generation, then exporting the most excellent individuality.The advantage of genetic algorithm is that it adopts parallel mode process multiple spot search problem, overcomes the defect that other single point search algorithms are easily absorbed in local optimum, is applicable to global path planning, easily searches globally optimal solution.Its shortcoming is that gene and controling parameters are difficult to decision-making, and algorithm may easily occur Premature Convergence and stagnation behavior.

Therefore, these algorithm application above still have in guided missile routeing much problem to be solved.And it is mostly the planning for single one piece of guided missile, do not consider from the angle that many bullets are collaborative.Therefore, these algorithms above all can not solve for the problem playing coordinated path planning from practical significance effectively.

Summary of the invention

For problems of the prior art, the present invention proposes a kind of many bullets based on multi-target evolution method and works in coordination with air route computing method, adopt collective search strategy for multi-objective Evolutionary Algorithm, only use based target functional value evaluation information, there is the feature of Implicit Parallelism, parallel computation; In conjunction with many-sided information such as performance of the geography information in planning region, position coordinates between ourselves and the enemy and motion conditions, the distribution of local antiaircraft fire, weapon, devise a kind of many bullets based on multi-objective Evolutionary Algorithm coordinated path planning method.The method provided in the present invention is different from now methodical notable feature and is: one, is applied to by multi-objective Evolutionary Algorithm and solves many bullet coordinated path planning problems, make use of global search and the computation capability of multi-objective Evolutionary Algorithm well; Its two, when environmental modeling, propose a kind of environmental modeling method that planning environment equal portions are split perpendicular to the parallel lines of launching site and impact point line by employing, be called for short parallel halving method.The constraint of partial target function is introduced wherein, thus simplifies the constraint of multi-objective Evolutionary Algorithm in evolutionary computation, be conducive to shortening the evolutionary computation time, improve efficiency of evolution; Its three, the present invention is directed to many bullets and carry out collaborative planning, differ from and traditional carry out routeing for single one piece of bullet.In planning, take into full account the Steric clashes relation between many bullets and attack relation time of arrival, be conducive to realizing multiple unfriendly target being carried out to setting-up time attack, carrying out saturation attack etc. to certain unfriendly target simultaneously, improve and attack efficiency.

The invention discloses a kind of many bullets based on multi-objective Evolutionary Algorithm and work in coordination with air route computing method, mainly comprise following step:

Step one: encoded in guided missile air route and define the maneuvering characteristics of guided missile;

Step 2: according to geographic location, naval vessel between ourselves and the enemy, determine a square planning region that can comprise naval vessel between ourselves and the enemy, in conjunction with environment and the motion on naval vessel and the firepower distribution situation between ourselves and the enemy in planning region, modeling is carried out to environment, adopt many parallel lines perpendicular to MISSILE LAUNCHING point and impact point line by the equidistant segmentation from launching site of the line between MISSILE LAUNCHING point and impact point, distance between adjacent two parallel lines is Length_Min, and the barrier of planning regional environment is divided into island and naval vessel between ourselves and the enemy; Island are simplified to the polygon no-fly zone represented with a series of longitude and latitude point; With position, naval vessel for the center of circle, the circular no-fly zone being radius to threaten radius represents its position, and the headway on naval vessel characterizes by the translational speed in the center of circle of circular no-fly zone, more circular no-fly zone is extended to the square no-fly zone tangent with circle;

Step 3: generate air route initial population P ₁, P ₂... P _n.

The equidistant split plot design modeling of many parallel lines perpendicular to launching site and impact point is adopted to planning environment, parallel lines through launching site are Article 1 parallel lines, and the air route between Article 1 parallel lines and Article 2 parallel lines is the 1st section of air route, if i represents i-th section of air route, distance between adjacent two parallel lines is Length_Min, and position angle, i-th section of air route and the i-th-1 azimuthal declinate of parallel lines are α _i, each bar parallel lines between launching site to impact point are respectively got a point as way point, each way point on launching site, each bar parallel lines and impact point are connected, determine an air route; If i-th way point coordinate on certain air route is (x _i, y _i), position angle and the distance of i-th way point to the i-th+1 way point are respectively angle _iand length _i, then have:

angle _i＝S_G_Angle-90°+α _i

length _i＝Length_Min/sinα _i

According to Vincent formula, obtained the latitude and longitude coordinates of each way point on a course line successively by impact point, change the azimuth value angle of i-th way point to the i-th+1 way point _i, change α _i, determine the latitude and longitude coordinates of next way point, the air route that corresponding generation one is different, choose the individual different α of m _ivalue generates the different air route of m bar, and form an initial population, symbiosis becomes n air route initial population P ₁, P ₂... P _n;

Step 4: to air route initial population P ₁, P ₂... P _ncarry out evolutional operation respectively, produce air route of new generation population, evolutional operation method has intersection, variation and level and smooth;

Step 5: the fitness value calculating each air route in each population in the population of air route of new generation, removes the air route of fitness difference, retains the air route of fitness optimum in each population, obtains the air route population P ' of fitness optimum ₁, P ' ₂... P ' _n, adopt the evaluation function for air route ideal adaptation degree to evaluate the air route in each population;

Fitness function f (m) of air route individuality is:

f(m)＝δ _dD(m)+δ _sS(m)+δ _cC(m)； (5)

Wherein, D (m) represents total voyage in an air route, and S (m) represents the smoothness in air route, and C (m) represents the safe coefficient in air route; δ _d, δ _s, δ _crepresent voyage, smoothness, the safe coefficient weight in fitness function respectively; F (m) is less, and air route individuality is more excellent; Wherein parameters definition is respectively with computing formula:

$\left\{\begin{array}{c}D\left(m\right)=\underset{i=1}{\overset{t-1}{\mathrm{\Σ}}}{\mathrm{length}}_i\\ {\mathrm{length}}_i\≥\mathrm{Length}\_\mathrm{Min},(i=\mathrm{1,2},...t-1)\\ D\left(m\right)\≤\mathrm{Route}\_\mathrm{Length}\_\mathrm{Max}\\ t\≤\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\end{array}\right.$

$\left\{\begin{array}{c}S\left(m\right)=\underset{i=1}{\overset{t-2}{\mathrm{\Σ}}}({\mathrm{angle}}_{i+1}-{\mathrm{angle}}_i)/(t-2)\\ ({\mathrm{angle}}_{i+1}-{\mathrm{angle}}_i)\≤\mathrm{Angle}\_\mathrm{Max},(i=\mathrm{1,2},...t-2)\\ t\≤\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\\ \end{array}\right.$

$\left\{\begin{array}{c}C\left(m\right)=1/\underset{i=1}{\overset{t-1}{\mathrm{\Σ}}}{l}_i\\ l_i>0,(i=\mathrm{1,2},...,t-1)\\ t\≤\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\\ \end{array}\right.$

Length _i, angle _irepresent the distance and bearing angle of i-th navigation spots to (i+1) individual navigation spots respectively, t represents the total number of waypoint navigation point, comprises launching site and impact point, l _irepresent length _ithe minor increment of the no-fly zone in Duan Hanglu distance planning region, l _iduring > 0, air route is not crossing with no-fly zone, works as l _iwhen=0, illustrate that air route section is crossing with no-fly zone, the angle of turning round of all navigation spots in air route can not exceed the steering locking angle Angle_Max of permission, does not comprise launching site and impact point; All air routes segment length in air route can not be less than the minimum air route segment distance Length_Min of permission; Total voyage in air route can not exceed the ultimate run Route_Length_Max of permission, and total navigation spots number in air route comprises the maximum number Route_Node_Num_Max that turns round that launching site and impact point can not exceed permission;

Calculate the mean square deviation D of the air route ideal adaptation angle value that each population comprises in the population of every generation air route, if the mean square deviation D of the air route ideal adaptation angle value of each population is all less than the mean square deviation numerical value of the fitness value of the air route individuality preset, from each population, then choose the minimum air route of fitness value f (m) as optimal air line, the air route set Q of composition different population, if the mean square deviation D of the air route ideal adaptation angle value of arbitrary population is not less than the mean square deviation numerical value of the fitness value of the air route individuality preset in the population of every generation air route, then return step 4, be optimized operation, until the mean square deviation D of the air route ideal adaptation angle value of each population is all less than the mean square deviation numerical value of the fitness value of the air route individuality preset in the population of every generation air route, the air route then choosing a fitness optimum from each population constitutes air route set Q, now air route set is the air route set between population,

Step 6: carry out evolutional operation to the air route set Q between population, obtain air route of new generation set Q ', the evolutional operation method of design comprises: between population, air route distance disturbance variation, air route voyage disturbance make a variation and smoothly make a variation;

Step 7: obtain air route of new generation set Q ' after air route set Q is evolved, evaluate the constraint whether it meets fitness function between population, adopt ideal adaptation degree evaluation function whether to satisfy condition to each air route individuality in set Q ' in air route of new generation simultaneously;

Fitness function D (n) wherein between population is:

$\left\{\begin{array}{c}D\left(n\right)=\underset{i=1}{\overset{t}{\mathrm{MIN}}}\left\{\mathrm{dis}\tan \mathrm{ce}(p_i,p_{i+1})\right\},(i=\mathrm{1,2},...t-1)\\ D\left(n\right)\≥D_{\min }\end{array}\right.---\left(9\right)$

$\left\{\begin{array}{c}T\left(n\right)=\underset{i=1}{\overset{t}{\mathrm{MIN}}}\left\{\mathrm{time}(S_i,S_{i+1})\right\},(i=\mathrm{1,2},...t-1)\\ T\left(n\right)\≥\mathrm{\Δt}\end{array}\right.---\left(10\right)$

Wherein dis tan ce (p _i, p _i+1) represent that the minor increment in two adjacent air routes of Q ' space is gathered in air route, time (S _i, S _i+1) represent that the launch time in two air routes that launch time is adjacent is poor, D _minthe minimum separation distances in two air routes that representation space is adjacent, Δ t represents the minimum time interval of launch requirements, and T (n) represents that the minimum launch time in the air route that all launch times are adjacent is poor;

In this step air route individual adopt ideal adaptation degree evaluation function identical with the fitness function in step 5;

Step 8: step 8: the mean square deviation E obtaining the fitness value between the air route set Q ' population of new generation after evolving according to the fitness function in step 7 between population, obtain the mean square deviation D ' of the fitness value in every bar air route in the set Q ' in air route of new generation after evolving with individual fitness function simultaneously, if E is less than the mean square deviation numerical value of the fitness value between the population that presets, D ' is also less than the mean square deviation numerical value of the fitness value of the air route individuality preset, then meet the cooperation condition between each air route, Output rusults; Otherwise any one does not meet, then return step 6, continue to carry out evolutional operation, until meet above-mentioned cooperation condition to air route set Q.

The invention has the advantages that:

The first, a kind of air route of many bullets based on multi-objective Evolutionary Algorithm cooperated computing method that the present invention proposes, is combined this multi-target non-linear problem of routeing with multi-objective Evolutionary Algorithm.The objective function utilizing multi-target evolution to calculate evaluates the feature of mechanism and parallel computation, the good many-sided constraint such as geography information, position coordinates between ourselves and the enemy and motion conditions, the antiaircraft fire distribution of enemy, the performance of weapon having processed the planning region related in many bullets routeing, searches out the air route of global optimum.Apply the feature of multi-objective Algorithm well, solve many bullet routeing problems rightly.

The second, a kind of air route of many bullets based on multi-objective Evolutionary Algorithm cooperated computing method that the present invention proposes, when environmental modeling, proposes a kind of environmental modeling method that planning environment equal portions are split perpendicular to the parallel lines of launching site and impact point line by employing.Be incorporated among model by the partially restrained condition of guided missile self and environmental constraint, the distance between vertical line is the bee-line required between 2, guided missile air route; By parallel halving method modeling, draw the method that the present invention sets up initial population: rely on and change current way point to the position angle of next way point and the azimuthal declinate of current point place parallel lines, determine initial population.Thus simplifying the objective function of evolution algorithm, accelerating algorithm planning process, when efficiently avoid evolutionary computation, calculated amount is excessive, consuming time long, thus improves efficiency of evolution.

3rd, a kind of air route of many bullets based on multi-objective Evolutionary Algorithm cooperated computing method that the present invention proposes, has abandoned conventional needle and has carried out routeing pattern to single one piece of guided missile, but carried out collaborative planning to many bullets.In planning, take into full account the Steric clashes relation between many bullets and attack relation time of arrival, be conducive to realizing multiple unfriendly target being carried out to setting-up time attack, carrying out saturation attack etc. to certain unfriendly target simultaneously, improve and attack efficiency.

Accompanying drawing explanation

Fig. 1: what the present invention proposed carries out the process flow diagram playing air route computing method based on multi-objective Evolutionary Algorithm more;

Fig. 2: to the modeling figure of planning regional environment in the present invention.

Embodiment

Below in conjunction with accompanying drawing, the present invention is described in detail.

Being platform with electronic chart, take Anti-ship Missile Route as application background.Because anti-warship guided missle cruise section distance sea level is lower, the routeing under two dimensional surface only can be considered.

A kind of Route planner of many bullets based on multi-objective Evolutionary Algorithm that the present invention proposes, as Fig. 1, specifically comprises following step:

Step one: encoded in guided missile air route and define the maneuvering characteristics of guided missile.The air route of guided missile is made up of one group of orderly navigation spots, and each navigation spots comprises the latitude and longitude value information of this point.Thus, navigation spots coding route_node is:

route_node＝{x，y，angle} (1)

Wherein, x, y represent the latitude and longitude coordinates (two-dimensional space planning) of this navigation spots respectively, adopt real coding; Angle represents the position angle of this navigation spots and next navigation spots.

Air route coding missile_route is:

missile_route＝{list<route_node>route_list，fitness_value，route_length，feasible_flag，sum_turn_angle，...}

(2)

Wherein, list<route_node>route_list is the navigation spots chained list collection information in this air route, fitness_valu is air route fitness value, route_length is the total length in air route, feasible_flag is the whether feasible mark amount in air route, and sum_turn_angle is the angle of always turning round in air route.

Comprising of the maneuvering characteristics of described guided missile:

1. position angle: be 0 degree of position angle with direct north, clockwise direction position angle is just, span is [0,360];

2. the steering locking angle of air route permission: Angle_Max;

3. the minimum air route segment distance of air route permission: Length_Min;

4. the ultimate run of air route permission: Route_Length_Max;

5. a maximum number: the Route_NodeNum_Max that turns round of air route permission;

6. the minimum separation distances in adjacent two air routes: D _min;

7. the minimum time interval of launch requirements: Δ t.

Step 2: according to geographic location, naval vessel between ourselves and the enemy, determines a square planning region that can comprise naval vessel between ourselves and the enemy, as figure, shown in 2.In conjunction with environment and the motion on naval vessel and the firepower distribution situation between ourselves and the enemy in planning region, modeling is carried out to environment.Adopt many parallel lines perpendicular to MISSILE LAUNCHING point and impact point line by the equidistant segmentation from launching site of the line between MISSILE LAUNCHING point and impact point, parallel lines wherein through launching site are Article 1 parallel lines, distance between adjacent two parallel lines is Length_Min, if the distance between a certain bar parallel lines and impact point is greater than Length_Min and is less than 2 × Length_Min, then no longer insert parallel lines between this parallel lines and impact point, these parallel lines are as the last item parallel lines.The barrier of planning regional environment can be divided into two classes substantially: island and between ourselves and the enemy naval vessel.Wherein island can be simplified to the polygon no-fly zone represented with a series of longitude and latitude point; Naval vessel when carrying out modeling with position, naval vessel for the center of circle, the circular no-fly zone being radius to threaten radius represents its position, the headway on naval vessel characterizes by the translational speed in the center of circle of circular no-fly zone, more circular no-fly zone is extended to the square no-fly zone tangent with circle.As shown in Figure 1: S point is launching site, G is impact point; F1 and F4 represents naval vessel between ourselves and the enemy, and F2, F3 and F5 represent the polygon no-fly zone of island after simplifying.L1 to L5 splits perpendicular to the equal portions of launching site and impact point line the parallel lines planning region.

Step 3: generate air route initial population P ₁, P ₂... P _n.

As Fig. 2, to generate an air route in an initial population, initial population can produce randomly, the air route population adopting random device to produce generally can cover whole planning region, there is certain popularity, but the air route feasibility adopting random device to produce is not high, increase search time.By adopting the equidistant split plot design modeling of many parallel lines perpendicular to launching site and impact point to planning environment in the present invention, propose a kind of new initial population generation method can accelerating planning process.As shown in Figure 1, S point is launching site, G point is impact point, parallel lines through launching site are Article 1 parallel lines, and the air route between Article 1 parallel lines and Article 2 parallel lines is the 1st section of air route, if i represents i-th section of air route, the distance between adjacent two parallel lines is Length_Min, and position angle, i-th section of air route and the i-th-1 azimuthal declinate of parallel lines are α _i, such as, from launching site, azimuthal declinate of the 1st section of position angle, air route and the 0th article of parallel divisional line L0 is α ₁.Due to S point and G point known, the distance and bearing angle S_G_Angle of S point to G point can be obtained by Vincent formula.On each bar parallel lines between S point to G point, (L1, L2, L3 and L4) respectively gets a point as way point, each way point S point and (L1, L2, L3, L4) on each bar parallel lines got and G point are connected, and just can determine an air route.If i-th way point coordinate on certain air route is (x _i, y _i), position angle and the distance of i-th way point to the i-th+1 way point are respectively angle _iand length _i, then have:

angle _i＝S_G_Angle-90°+α _i (3)

length _i＝Length_Min/sinα _i (4)

According to Vincent formula, when more known latitude and longitude coordinates and this point arrive the azimuth-range of required point, the latitude and longitude coordinates of impact point can be obtained, then can be obtained the latitude and longitude coordinates of each way point on a course line by S point successively.Therefore the azimuth value angle of change i-th way point to the i-th+1 way point is only needed _i, namely change α _i, just can determine the latitude and longitude coordinates of next way point.And α _ibe an anglec of rotation, this angular configurations is chosen arbitrarily in [0,180], therefore, chooses arbitrarily a different α _ivalue, the air route that corresponding generation one is different, chooses the individual different α of m _ivalue can generate the different air route of m bar, and this m bar air route forms an initial population P.The general value of m is between 30 to 50, and numerical value is larger, and between the whole planning region of covering that can be better, but evolutionary process is consuming time also longer.Thus enable air route population cover whole planning space.Need it is specifically intended that application claims is at selection α _ishi Buneng makes the no-fly zone on guided missile air route section and island or naval vessel between ourselves and the enemy crossing.Using such method, symbiosis becomes n air route initial population P ₁, P ₂... P _n, all containing m bar air route in each population.

Step 4: to air route initial population P ₁, P ₂... P _ncarry out evolutional operation respectively, produce air route of new generation population, population number is consistent, or n population, also comprises m bar air route respectively in each population.Design following evolutional operation method, any one or a few evolutional operation following can be taked respectively to the air route in same population respectively, generate air route of new generation population.

(1) intersect: adopt two point to intersect.Two air routes are chosen arbitrarily as parent in initial population, on two parents respectively random selecting two way points as point of crossing (launching site and impact point except), two air routes are broken into two parts respectively from point of crossing, then the Part I of first parent and the Part II of second parent combine, the Part I of the Part II of first parent and first parent combines, thus the air route that generation two is new.

(2) make a variation: mutation operation is the important channel keeping species diversity, is not only regarded as the means obtaining losing excellent genes because of interlace operation, or explore the powerful of adjacent space, Optimal performance.The present invention is directed to the inner Evolutionary Design of air route initial population three kinds of variation methods, can use or optional one use simultaneously:

Delete variation---random erasure navigation spots (launching site and impact point except) from air route individuality and any air route, generates a new air route;

Disturbance makes a variation---change the coordinate of certain navigation spots in air route individuality and any air route, for navigation spots whether in barrier or the air route, two sections, front and back connecting this point whether intersect with barrier, different ranges of disturbance is set, specific practice is certain navigation spots chosen is the center of circle, be that radius draws circle with r, disturbance region choosing is away from the half-circle area of barrier.If this navigation spots is in barrier, r gets the distance of this navigation spots to this barrier farthest vertices, if this point is not in barrier, r get the minimum air route segment distance that air route allows 1/5 (this numerical value need adjust in conjunction with practical situations, be 1/5 under normal circumstances), i.e. 1/5Length_Min;

2 variations---select adjacent two navigation spots in air route individuality and any air route (launching site and impact point except), regenerate two navigation spots, two navigation spots that replacement is chosen.Concrete operation method can refer to the method generating air route in initial population, changes the value choosing a corresponding position angle, i-th section of air route and the i-th-1 parallel lines azimuthal declinate α i respectively, generates two new way points, the navigation spots that replacement is chosen.

(3) level and smooth: smoothing operator designs for the steering locking angle of guided missile, by this smooth operation realize air route turning angle be less than air route allow steering locking angle Angle_Max, under normal circumstances, the value of air route turning angle is (Angle_Max-30 °).From the method generating initial population air route, change position angle, i-th section of air route and the i-th-1 azimuthal declinate α of parallel lines _i, both can obtain different way points, and α _ivalue, between [0,180], works as α _itime value is more tending towards 0 degree or 180 degree, the angle of turning round of this point is larger, and when being more tending towards in the middle of [0,180] (being generally [110,145]), and this some angle of turning round is less.Change α _ivalue make to diminish to angle of turning round should be put, the level and smooth of air route can be realized, simultaneously also shortened the total length in path.

Step 5: the fitness value calculating each air route in each population in the population of air route of new generation, removes the air route of fitness difference, retains the air route of fitness optimum in each population, obtains the air route population P ' of fitness optimum ₁, P ' ₂... P ' _n.Adopt and for the evaluation function of air route ideal adaptation degree, the air route in each population is evaluated.

Fitness function for air route individuality considers two factors: the feasibility in air route and the superiority-inferiority in air route.The feasibility assessment in air route comprises two aspects: get along well the constraint that barrier intersects, air route meets guided missile self performance in air route; The superior and inferior evaluating in air route comprises three aspects: total voyage in air route, the smoothness in air route, the safe coefficient in air route.Fitness function f (m) of air route individuality is:

f(m)＝δ _dD(m)+δ _sS(m)+δ _cC(m)； (5)

Wherein, D (m) represents total voyage in an air route, and total voyage is less, and missile flight time is shorter, brings error less in missile flight process.S (m) represents the smoothness in air route, and S (m) is less, illustrates that air route is more level and smooth, and the guided missile error brought of turning is less.C (m) represents the safe coefficient in air route, from no-fly zone more away from safer, namely C (m) is less, safer.δ _d, δ _s, δ _crepresent voyage, smoothness, the safe coefficient weight in fitness function respectively.As from the foregoing, f (m) is less, and air route individuality is more excellent.Wherein parameters definition is respectively with computing formula:

$\left\{\begin{array}{c}D\left(m\right)=\underset{i=1}{\overset{t-1}{\mathrm{\&Sigma;}}}{\mathrm{length}}_i\\ {\mathrm{length}}_i\&GreaterEqual;\mathrm{Length}\_\mathrm{Min},(i=\mathrm{1,2},...t-1)\\ D\left(m\right)\&le;\mathrm{Route}\_\mathrm{Length}\_\mathrm{Max}\\ t\&le;\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\end{array}\right.---\left(6\right)$

$\left\{\begin{array}{c}S\left(m\right)=\underset{i=1}{\overset{t-2}{\mathrm{\&Sigma;}}}({\mathrm{angle}}_{i+1}-{\mathrm{angle}}_i)/(t-2)\\ ({\mathrm{angle}}_{i+1}-{\mathrm{angle}}_i)\&le;\mathrm{Angle}\_\mathrm{Max},(i=\mathrm{1,2},...t-2)\\ t\&le;\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\\ \end{array}\right.---\left(7\right)$

$\left\{\begin{array}{c}C\left(m\right)=1/\underset{i=1}{\overset{t-1}{\mathrm{\&Sigma;}}}{l}_i\\ l_i>0,(i=\mathrm{1,2},...,t-1)\\ t\&le;\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\\ \end{array}\right.---\left(8\right)$

Length _i, angle _irepresent the distance and bearing angle of i-th navigation spots to (i+1) individual navigation spots respectively, t represents the total number of waypoint navigation point (comprising launching site and impact point), l _irepresent length _ithe minor increment of the no-fly zone in Duan Hanglu distance planning region, l _iduring > 0, air route is not crossing with no-fly zone, works as l _iwhen=0, illustrate that air route section is crossing with no-fly zone.The angle of turning round of all navigation spots in air route (not comprising launching site and impact point) can not exceed the steering locking angle Angle_Max of permission.All air routes segment length in air route can not be less than the minimum air route segment distance Length_Min of permission.Total voyage in air route can not exceed the ultimate run Route_Length_Max of permission.Total navigation spots number (comprising launching site and impact point) in air route can not exceed a maximum number Route_Node_Num_Max that turns round for permission.

Calculate the mean square deviation D of the air route ideal adaptation angle value that each population comprises in the population of every generation air route, if the mean square deviation D of the air route ideal adaptation angle value of each population is all less than the mean square deviation numerical value of the fitness value of the air route individuality preset, from each population, then choose the minimum air route of fitness value f (m) as optimal air line, the air route set Q of composition different population, if the mean square deviation D of the air route ideal adaptation angle value of arbitrary population is not less than the mean square deviation numerical value of the fitness value of the air route individuality preset in the population of every generation air route, then return step 4, be optimized operation, until the mean square deviation D of the air route ideal adaptation angle value of each population is all less than the mean square deviation numerical value of the fitness value of the air route individuality preset in the population of every generation air route, the air route then choosing a fitness optimum from each population constitutes air route set Q, now air route set is the air route set between population.

Step 6: the air route choosing a fitness optimum from each population in step 5 constitutes air route set Q, now air route set is the air route set between population.Evolutional operation is carried out to the air route set Q between population, after air route set Q evolves, obtains air route of new generation set Q '.For the track line Existential Space conflict phenomenon in air route in the same time, and need the attack realized to require (as setting-up time attack, saturation attack etc.), from the viewpoint of room and time two Design evolution operator, air route individuality is carried out to the fine setting of local, to meet the harmony in air route between many pieces of guided missiles.The evolutional operation method of design is as follows:

(1) air route distance disturbance variation between population: must minimum value D be greater than for the distance in any two air routes in air route set Q _min, the most place of tapping into air route distance in air route set Q being less than to these value two air routes finely tunes.If Article 1 air route and Article 2 air route are respectively A and B closest to the way point located, way point A, B can move along air route, front and back two section of this point, when way point A moves on Article 1 air route, a direction must be had to be direction away from Article 2 air route, in like manner, when way point B moves on Article 2 air route, a direction must be had to be direction away from Article 1 air route.Way point A, B are moved according to the direction in air route, place away from each other, make its distance separately, the minor increment between two air routes is greater than minimum value D _min, then complete mutation operation, form new air route.When carrying out mutation operation, the individual constraint (namely meeting air route ideal adaptation degree evaluation function) in air route own need be met.

(2) air route voyage disturbance variation: minimum value Δ t must be greater than for the Transmission Time Interval in two air routes before and after guided missile, to two air routes that guided missile is successively launched, after determining its launch time, require that its Transmission Time Interval need be not less than Δ t, if do not meet, the voyage in a wherein air route need be adjusted.From the method generating initial population air route, change position angle, i-th section of air route and the i-th-1 azimuthal declinate α of parallel lines _i, both can obtain different way points, and α _ivalue, between [0,180], works as α _itime value is more tending towards 0 degree or 180 degree, the angle of turning round of this point is larger, and air route voyage is larger, and when being more tending towards [110,145] in the middle of [0,180], and this some angle of turning round is less, and air route voyage is less.Then can change α corresponding to any way point _ivalue, make air route voyage become large, make it satisfy condition.When carrying out mutation operation, need to meet the individual constraint (namely meeting air route ideal adaptation degree evaluation function) in air route own simultaneously.

(3) smoothly make a variation: in two air route sections that navigation spots is adjacent, insert new navigation spots respectively, the navigation spots line of new insertion is parallel to the line of the previous two adjacent phase navigation spots of change point, delete former navigation spots simultaneously, realize the level and smooth of air route, also shorten the total length in path simultaneously.

Various evolutional operation can carry out simultaneously above, also can optionally wherein severally carry out, and only need reach the object of evolutional operation.

Step 7: obtain set Q ' in air route of new generation after air route set Q evolves, evaluate the constraint whether it meets fitness function between population, adopt the evaluation of ideal adaptation degree evaluation function whether to satisfy condition to each air route individuality in set Q ' in air route of new generation simultaneously.Fitness function D (n) between population is:

$\left\{\begin{array}{c}D\left(n\right)=\underset{i=1}{\overset{t}{\mathrm{MIN}}}\left\{\mathrm{dis}\tan \mathrm{ce}(p_i,p_{i+1})\right\},(i=\mathrm{1,2},...t-1)\\ D\left(n\right)\&GreaterEqual;D_{\min }\end{array}\right.---\left(9\right)$

$\left\{\begin{array}{c}T\left(n\right)=\underset{i=1}{\overset{t}{\mathrm{MIN}}}\left\{\mathrm{time}(S_i,S_{i+1})\right\},(i=\mathrm{1,2},...t-1)\\ T\left(n\right)\&GreaterEqual;\mathrm{\&Delta;t}\end{array}\right.---\left(10\right)$

Wherein dis tan ce (p _i, p _i+1) represent that the minor increment in two adjacent air routes of Q ' space is gathered in air route, time (S _i, S _i+1) represent that the launch time in two air routes that launch time is adjacent is poor, D _minthe minimum separation distances in two air routes that representation space is adjacent, Δ t represents the minimum time interval of launch requirements, and T (n) represents that the minimum launch time in the air route that all launch times are adjacent is poor.

In this step air route individual adopt ideal adaptation degree evaluation function identical with the fitness function in step 5.

Step 8: the mean square deviation E obtaining the fitness value between the air route set Q ' population of new generation after evolving according to the fitness function in step 7 between population, obtains the mean square deviation D ' of the fitness value in every bar air route in the set Q ' in air route of new generation after evolving simultaneously with individual fitness function.If E is less than the mean square deviation numerical value of the fitness value between the population that presets, D ' is also less than the mean square deviation numerical value of the fitness value of the air route individuality preset, and namely meets the cooperation condition between each air route, Output rusults; Otherwise any one does not meet (as E is less than the mean square deviation numerical value of the fitness value between the population preset, but D ' is not less than the mean square deviation numerical value of the fitness value of the air route individuality preset, then do not meet the cooperation condition between each air route), then do not meet the cooperation condition between each air route, return step 6, continue to carry out evolutional operation, until meet cooperation condition to air route set Q.

Claims (5)

1. based on many bullets Route planner of multi-objective Evolutionary Algorithm, it is characterized in that: comprise following step:

Step one: encoded in guided missile air route and define the maneuvering characteristics of guided missile;

Step 2: according to geographic location, naval vessel between ourselves and the enemy, determine a square planning region that can comprise naval vessel between ourselves and the enemy, in conjunction with environment and the motion on naval vessel and the firepower distribution situation between ourselves and the enemy in planning region, modeling is carried out to environment, adopt many parallel lines perpendicular to MISSILE LAUNCHING point and impact point line by the equidistant segmentation from launching site of the line between MISSILE LAUNCHING point and impact point, distance between adjacent two parallel lines is Length_Min, and the barrier of planning regional environment is divided into island and naval vessel between ourselves and the enemy; Island are simplified to the polygon no-fly zone represented with a series of longitude and latitude point; With position, naval vessel for the center of circle, the circular no-fly zone being radius to threaten radius represents its position, and the headway on naval vessel characterizes by the translational speed in the center of circle of circular no-fly zone, more circular no-fly zone is extended to the square no-fly zone tangent with circle;

Step 3: generate air route initial population P ₁, P ₂... P _n:

The equidistant split plot design modeling of many parallel lines perpendicular to launching site and impact point is adopted to planning environment, parallel lines through launching site are Article 1 parallel lines, and the air route between Article 1 parallel lines and Article 2 parallel lines is the 1st section of air route, if i represents i-th section of air route, distance between adjacent two parallel lines is Length_Min, and position angle, i-th section of air route and the i-th-1 azimuthal declinate of parallel lines are α _i, each bar parallel lines between launching site to impact point are respectively got a point as way point, each way point on launching site, each bar parallel lines and impact point are connected, determine an air route; If i-th way point coordinate on certain air route is (x _i, y _i), position angle and the distance of i-th way point to the i-th+1 way point are respectively angle _iand length _i, then have:

angle _i＝S_G_Angle-90°+α _i

length _i＝Length_Min/sinα _i

S point is launching site, and G is impact point, and S_G_Angle is that S point is to G point position angle;

According to Vincent formula, obtained the latitude and longitude coordinates of each way point on a course line successively by impact point, change the azimuth value angle of i-th way point to the i-th+1 way point _i, change α _i, determine the latitude and longitude coordinates of next way point, the air route that corresponding generation one is different, choose the individual different α of m _ivalue generates the different air route of m bar, and form an initial population, symbiosis becomes n air route initial population P ₁, P ₂... P _n;

Step 4: to air route initial population P ₁, P ₂... P _ncarry out evolutional operation respectively, produce air route of new generation population, evolutional operation method has intersection, variation and level and smooth;

Step 5: the fitness value calculating each air route in each population in the population of air route of new generation, removes the air route of fitness difference, retains the air route of fitness optimum in each population, obtains the air route population P of fitness optimum ₁', P ₂' ... P _n', adopt the evaluation function for air route ideal adaptation degree to evaluate the air route in each population;

Fitness function f (m) of air route individuality is:

f(m)＝δ _dD(m)+δ _sS(m)+δ _cC(m)； (5)

Wherein, D (m) represents total voyage in an air route, and S (m) represents the smoothness in air route, and C (m) represents the safe coefficient in air route; δ _d, δ _s, δ _crepresent voyage, smoothness, the safe coefficient weight in fitness function respectively; F (m) is less, and air route individuality is more excellent; Wherein parameters definition is respectively with computing formula:

$\left\{\begin{array}{c}D\left(m\right)=\underset{i=1}{\overset{t-1}{\mathrm{\&Sigma;}}}{\mathrm{length}}_i\\ {\mathrm{length}}_i\&GreaterEqual;\mathrm{Length}\_\mathrm{Min},i=\mathrm{1,2},...,t-1\\ D\left(m\right)\&le;\mathrm{Route}\_\mathrm{Length}\_\mathrm{Max}\\ t\&le;\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\end{array}\right.$

$\left\{\begin{array}{c}S\left(m\right)=\underset{i=1}{\overset{t-2}{\mathrm{\&Sigma;}}}({\mathrm{angle}}_{i+1}-{\mathrm{angle}}_i)/(t-2)\\ ({\mathrm{angle}}_{i+1}-{\mathrm{angle}}_i)\&le;\mathrm{Angle}\_\mathrm{Max},i=\mathrm{1,2},...,t-2\\ t\&le;\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\end{array}\right.$

$\left\{\begin{array}{c}C\left(m\right)\text{=1/}\underset{i=1}{\overset{t-1}{\mathrm{\&Sigma;}}}{l}_i\\ l_i>0,i=\mathrm{1,2},...,t-1\\ t\&le;\mathrm{Route}\_\mathrm{Node}\_\mathrm{Num}\_\mathrm{Max}\end{array}\right.$

Length _i, angle _irepresent the distance and bearing angle of i-th way point to the i-th+1 way point respectively, t represents the total number of air route way point, comprises launching site and impact point, l _irepresent length _ithe minor increment of the no-fly zone in Duan Hanglu distance planning region, l _iduring > 0, air route is not crossing with no-fly zone, works as l _iwhen=0, illustrate that air route section is crossing with no-fly zone, the angle of turning round of all way points in air route can not exceed the steering locking angle Angle_Max of permission, does not comprise launching site and impact point; All air routes segment length in air route can not be less than the minimum air route segment distance Length_Min of permission;

Total voyage in air route can not exceed the ultimate run Route_Length_Max of permission, and total way point number in air route comprises the maximum number Route_Node_Num_Max that turns round that launching site and impact point can not exceed permission;

Calculate the mean square deviation D of the air route ideal adaptation angle value that each population comprises in the population of every generation air route, if the mean square deviation D of the air route ideal adaptation angle value of each population is all less than the mean square deviation numerical value of the fitness value of the air route individuality preset, from each population, then choose the minimum air route of fitness value f (m) as optimal air line, the air route set Q of composition different population, if the mean square deviation D of the air route ideal adaptation angle value of arbitrary population is not less than the mean square deviation numerical value of the fitness value of the air route individuality preset in the population of every generation air route, then return step 4, carry out evolutional operation, until the mean square deviation D of the air route ideal adaptation angle value of each population is all less than the mean square deviation numerical value of the fitness value of the air route individuality preset in the population of every generation air route, the air route then choosing a fitness optimum from each population constitutes air route set Q, now air route set is the air route set between population,

Step 6: carry out evolutional operation to the air route set Q between population, obtain air route of new generation set Q ', the evolutional operation method of design comprises: between population, air route distance disturbance variation, air route voyage disturbance make a variation and smoothly make a variation;

Step 7: obtain air route of new generation set Q ' after air route set Q is evolved, evaluate the constraint whether it meets fitness function between population, simultaneously individual to each air route in set Q ' in air route of new generation, evaluate the constraint whether it meets ideal adaptation degree evaluation function;

Fitness function D (n) wherein between population is:

$\left\{\begin{array}{c}D\left(n\right)=\underset{i=1}{\overset{t}{\mathrm{MIN}}}\left\{\mathrm{dis}\tan \mathrm{ce}(p_i,p_{i+1})\right\},i=\mathrm{1,2},...,t-1\\ D\left(n\right)\&GreaterEqual;D_{\min }\end{array}\right.---\left(9\right)$

$\left\{\begin{array}{c}T\left(n\right)=\underset{i=1}{\overset{t}{\mathrm{MIN}}}\left\{\mathrm{time}(S_i,S_{i+1})\right\},i=\mathrm{1,2},...,t-1\\ T\left(n\right)\&GreaterEqual;\mathrm{\&Delta;t}\end{array}\right.---\left(10\right)$

Wherein dis tan ce (p _i, p _i+1) represent that the minor increment in two adjacent air routes of Q ' space is gathered in air route, time (S _i, S _i+1) represent that the launch time in two air routes that launch time is adjacent is poor, D _minthe minimum separation distances in two air routes that representation space is adjacent, Δ t represents the minimum time interval of launch requirements, and T (n) represents that the minimum launch time in the air route that all launch times are adjacent is poor;

In this step air route individual adopt ideal adaptation degree evaluation function identical with the fitness function in step 5;

Step 8: the mean square deviation E obtaining the fitness value between the air route set Q ' population of new generation after evolving according to the fitness function in step 7 between population, obtain the mean square deviation D ' of the fitness value in every bar air route in the set Q ' in air route of new generation after evolving with individual fitness function simultaneously, if E is less than the mean square deviation numerical value of the fitness value between the population that presets, D ' is also less than the mean square deviation numerical value of the fitness value of the air route individuality preset, then meet the cooperation condition between each air route, Output rusults; Otherwise any one does not meet, then return step 6, continue to carry out evolutional operation, until meet above-mentioned cooperation condition to air route set Q.

2. a kind of Route planner of many bullets based on multi-objective Evolutionary Algorithm according to claim 1, it is characterized in that: in described step one, coding is carried out to guided missile air route and be specially: the air route of guided missile is made up of one group of orderly way point, each way point comprises the latitude and longitude value information of this point, way point coding route_node is: route_node={x, y, angle}; Wherein, x, y represent the latitude and longitude coordinates of this way point respectively, adopt real coding; Angle represents the position angle of this way point and next way point;

Air route coding missile_route is:

missile_route＝{list＜route_node＞route_list,fitness_value,route_length,feasible_flag,sum_turn_angle}

Wherein, list < route_node > route_list is the way point chained list collection information in this air route, fitness_value is air route fitness value, route_length is the total length in air route, feasible_flag is the whether feasible mark amount in air route, and sum_turn_angle is the angle of always turning round in air route.

3. a kind of Route planner of many bullets based on multi-objective Evolutionary Algorithm according to claim 1, is characterized in that: in described step one, the maneuvering characteristics of guided missile comprises:

1. position angle: be 0 degree of position angle with direct north, clockwise direction position angle is just, span is [0,360];

2. the steering locking angle of air route permission: Angle_Max;

3. the minimum air route segment distance of air route permission: Length_Min;

4. the ultimate run of air route permission: Route_Length_Max;

5. a maximum number: the Route_Node_Num_Max that turns round of air route permission;

6. the minimum separation distances in adjacent two air routes: D _min;

The minimum time interval of launch requirements: Δ t.

4. a kind of Route planner of many bullets based on multi-objective Evolutionary Algorithm according to claim 1, is characterized in that: intersect in described step 4, make a variation and be smoothly specially:

(1) intersect: adopt two point to intersect, two air routes are chosen arbitrarily as parent in initial population, on two parents, difference random selecting two way points are as point of crossing, except launching site and impact point, two air routes are broken into two parts respectively from point of crossing, then the Part I of first parent and the Part II of second parent combine, and the Part I of the Part II of first parent and first parent combines, thus the air route that generation two is new;

(2) make a variation: for the inner Evolutionary Design of air route initial population three kinds of variation methods:

Delete variation: random erasure way point from air route individuality and any air route, except launching site and impact point, generate a new air route;

Disturbance makes a variation: the coordinate changing certain way point in the individuality of air route, for way point whether in barrier or the air route, two sections, front and back connecting this point whether intersect with barrier, different ranges of disturbance is set, certain way point being specially to choose is the center of circle, be that radius draws circle with r, disturbance region choosing is away from the half-circle area of barrier, if this way point is in barrier, r gets the distance of this way point to this barrier farthest vertices, if this point is not in barrier, r gets 1/5,1/5Length_Min of the minimum air route segment distance that air route allows;

2 variations: select adjacent two way points in air route individuality and any air route, except launching site and impact point, regenerate two way points, replace two way points chosen, with reference to the method generating air route in initial population, change respectively and choose a corresponding position angle, i-th section of air route and the i-th-1 azimuthal declinate α of parallel lines _ivalue, generate two new way points, replace the way point chosen;

(3) level and smooth: smoothing operator designs for the steering locking angle of guided missile, by smooth operation realize air route turning angle be less than air route allow steering locking angle Angle_Max, the value of air route turning angle is (Angle_Max-30 °), position angle, i-th section of air route and the i-th-1 azimuthal declinate α of parallel lines _ivalue, between [0,180], works as α _itime value is more tending towards 0 degree or 180 degree, the angle of turning round of this way point is larger, and is more tending towards [110,145], and this way point angle of turning round is less, changes α _ivalue make, to diminishing at way point angle of turning round, to realize the level and smooth of air route.

5. a kind of Route planner of many bullets based on multi-objective Evolutionary Algorithm according to claim 1, is characterized in that: in described step 6, between population, air route distance disturbance variation, air route voyage disturbance variation and level and smooth variation are specially:

(1) air route distance disturbance variation between population: must minimum value D be greater than for the distance in any two air routes in air route set Q _min, finely tuning closest to place of these value two air routes is less than to air route distance in air route set Q, if Article 1 air route and Article 2 air route are respectively A and B closest to the way point located, way point A, B can move along air route, front and back two section of this point, when way point A moves on Article 1 air route, a direction must be had to be direction away from Article 2 air route, in like manner, when way point B moves on Article 2 air route, a direction must be had to be direction away from Article 1 air route, by way point A, B moves according to the direction in air route, place away from each other, make its distance separately, minor increment between two air routes is greater than minimum value D _min, then complete mutation operation, form new air route,

(2) air route voyage disturbance variation: minimum value Δ t must be greater than for the Transmission Time Interval in two air routes before and after guided missile, to two air routes that guided missile is successively launched, after determining its launch time, require that its Transmission Time Interval need be not less than Δ t, if do not meet, the voyage in a wherein air route need be adjusted, from the method generating initial population air route, change position angle, i-th section of air route and the i-th-1 azimuthal declinate α of parallel lines _i, different way points can be obtained, and α _ivalue, between [0,180], works as α _itime value is more tending towards 0 degree or 180 degree, the angle of turning round of this way point is larger, and air route voyage is larger, and when being more tending towards [110,145], and this way point angle of turning round is less, and air route voyage is less, then change the α that any way point is corresponding _ivalue, make air route voyage become large, make it satisfy condition;

(3) smoothly make a variation: in two air route sections that way point is adjacent, insert new way point respectively, the way point line of new insertion is parallel to the line of the previous two adjacent way points of change point, delete former way point simultaneously, realize the level and smooth of air route, also shorten the total length in path simultaneously.