CN110046460A - A kind of amphibious vehicle Boulez optimization method based on adaptive elite genetic algorithm - Google Patents
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Abstract
The present invention relates to a kind of amphibious vehicle Boulez optimization methods based on adaptive elite genetic algorithm.The present invention includes: to obtain amphibious vehicle and Boulez bulk；Specify amphibious vehicle Boulez constraint condition；Determine amphibious vehicle Boulez objective function；Set adaptive elite genetic algorithm initial parameter；First generation amphibious vehicle Boulez kind group coding is randomly generated；Contemporary individual adaptation degree is resolved, saves optimum individual as elite individual；Judge whether that reaching maximum number of iterations or average fitness reaches desired value；The difference of all individuals and worst individual adaptation degree is as all new fitness of individual；Hereditary selection, intersection and variation are carried out, population of new generation is generated；Elite individual replaces the worst individual of population of new generation；Optimum individual in last generation population is decoded, the optimal ordering of vehicle Boulez is obtained；Amphibious vehicle cloth column position is determined using level of subsistence location algorithm.
Description
(1) technical field
The present invention is a kind of amphibious vehicle Boulez optimization method based on adaptive elite genetic algorithm.
(2) background technique
Amphibious warfare is that the ground force of one's own side and air power are thrown to hostile seashore by surface ship or specified
Seabeach.Under administrative loading mode, when " wasp grade " amphibious assault ship executes task, loading target is to maximize vehicle
Cabin floor space utilization rate.
The essence of the vehicle Boulez problem of amphibious assault ship is rectangle two dimension layout, belongs to one kind of combinatorial optimization problem.
The purpose of Boulez is to solve optimal alignment mode in a limited space, usually solves approximate optimal solution using intelligent algorithm.With excellent
Change the development of algorithm, the performances such as speed and precision of algorithm are greatly improved.New optimization algorithm is applied to two dimension
Cutting Stock Problem is the hot spot studied now.C.Alves is proposed based on the searching algorithm for becoming field, solves irregular seat parts
The optimal location problem in unprocessed cladding.
But the resolving time of traditional genetic algorithm is long, convergence rate is slow, it is possible to produce degenerates.Genetic algorithm is root
Current individual is selected according to fitness size, with the increase of algorithm iteration number, when individual adaptation degree in former generation population
Difference can very little, more outstanding individual will not occupy very big advantage in the selection process, eventually lead to the outstanding journey of solution
It spends lower.For this purpose, it is an object of the invention to propose the amphibious vehicle Boulez optimization method based on adaptive elite genetic algorithm.
(3) summary of the invention
The purpose of the present invention is to provide a kind of amphibious vehicle Boulez optimization methods based on adaptive elite genetic algorithm.
The object of the present invention is achieved like this:
(1) amphibious vehicle and Boulez bulk are obtained；
(2) clear amphibious vehicle Boulez constraint condition；
(3) amphibious vehicle Boulez objective function is determined；
(4) adaptive elite genetic algorithm initial parameter is set；
(5) first generation amphibious vehicle Boulez kind group coding is randomly generated；
(6) contemporary individual adaptation degree is resolved, saves optimum individual as elite individual；
(7) judge whether that reaching maximum number of iterations or average fitness reaches desired value, if it is goes to step
(11), step (8) are otherwise gone to；
(8) all individuals are with the difference of worst individual adaptation degree as all new fitness of individual；
(9) hereditary selection, intersection and variation are carried out, population of new generation is generated；
(10) elite individual replaces the worst individual of population of new generation, goes to step (6)；
(11) optimum individual in last generation population is decoded, obtains the optimal ordering of vehicle Boulez；
(12) amphibious vehicle cloth column position is determined using level of subsistence location algorithm；
(13) amphibious vehicle Boulez is completed.
The advantages of the invention is: first point, the calculating time of traditional genetic algorithm is long, and convergence rate is slow, in iteration mistake
It is possible to generate degeneration, the i.e. average fitness of the filial generation phenomenon lower than parent in journey.Adaptive elite genetic algorithm introduces essence
English strategy improves problem above.The population for being n for size saves fitst water individual (elite individual) before selection operation.
After the completion of each genetic manipulation, worst individual is replaced with into current elite individual.Guarantee the fitst water individual of every generation directly
It is influenced into the next generation, and not by genetic manipulation.Elitism strategy can accelerate the convergence rate of genetic algorithm, weaken iteration mistake
Population deterioration phenomenon in journey.Second point, traditional genetic algorithm is to select excellent individual according to fitness size, with iteration time
Number increases, and individual adaptation degree difference very little reduces the advantage of excellent individual, and the outstanding degree for eventually leading to solution reduces.In order to
Problem above is solved, before selection operation, replaces former adapt to using the fitness of all individuals and the difference of minimum fitness
Degree.For every generation population, the foundation of selection operation is current new environment, effectively avoids the competing of excellent individual after successive ignition
Strive the case where power weakens.Traditional self-adapted genetic algorithm is by changing crossover probability and variation, so that algorithm more adapts to
In current living environment.The adaptive strategy mentioned is the probability selected by each individual of adaptively changing, that is, adjusts life
Dis environment makes it survive more suitable for excellent individual, to improve excellent individual competitiveness.With traditional self-adapted genetic algorithm
It compares, the calculating process of mentioned self-adapted genetic algorithm is simple, does not need to solve complicated function, can substantially reduce calculating
Amount, to improve algorithm computational efficiency.The present invention, which demonstrates adaptive elite heredity Boulez optimization algorithm by emulation experiment, to be had
Effect property.
(4) Detailed description of the invention
Fig. 1 is the amphibious vehicle Boulez optimization method flow diagram based on adaptive elite genetic algorithm；
Fig. 2 is the amphibious vehicle Boulez figure based on traditional genetic algorithm；
Fig. 3 is the amphibious vehicle Boulez figure based on simulated annealing；
Fig. 4 is the amphibious vehicle Boulez figure based on adaptive elite genetic algorithm；
Fig. 5 is the fitness change curve based on traditional genetic algorithm；
Fig. 6 is the fitness change curve based on simulated annealing；
Fig. 7 is the fitness change curve based on adaptive elite genetic algorithm.
(5) specific embodiment
Present invention will now be described in detail with reference to the accompanying drawings.:
As shown in Figure 1, the invention discloses a kind of amphibious vehicle Boulez optimization sides based on adaptive elite genetic algorithm
Method.Realization of the invention the following steps are included:
(1) amphibious vehicle and Boulez bulk are obtained；
Related amphibious vehicle and Boulez bulk are as follows: the cloth column space of vehicle hold rectangle is P, a length of L, and width is
W, there are n vehicle { Pi, i=1...n }, length and width is respectively liAnd wi, in the plan view from above of vehicle hold deck, if left
Inferior horn is origin O (0,0), and the upper left corner is (0, L), and the lower right corner is (W, 0), rectangle vehicle PiTop left corner apex be (xi1,yi1),
Then PiBottom right angular coordinate is
(2) clear amphibious vehicle Boulez constraint condition；
Related constraint condition are as follows: two vehicle PiAnd Pj(i ≠ j) is not overlapped, vehicle cannot be placed on cloth column space it
Outside, while the height of vehicle and width are greater than 0, and every kind of vehicle can all have the limitation of maximum quantity, numrIt is r type vehicle cloth
The quantity of column, NrIt is the maximum quantity of r kind vehicle, constrains as follows:
(3) amphibious vehicle Boulez objective function is determined；
Related objective function is that vehicle hold deck nonavailability is minimum, i.e. the sum of Boulez area maximum shared by vehicle,
It indicates are as follows:
(4) adaptive elite genetic algorithm initial parameter is set；
Related initial parameter are as follows: the number of iterations is 100 times, Population Size 100, crossover probability 0.9, and variation is general
Rate is 0.15；
(5) first generation amphibious vehicle Boulez kind group coding is randomly generated；
Related population generates are as follows: the mode for generating initial population is chromosome corresponding constituted using random number
Body forms initial population, and amphibious vehicle Boulez problem can be converted into the combinatorial optimization problem of vehicle parking sequence, chooses the decimal system
Car number is coding mode, such as coded sequence is { 1,5,2,6,3,4 }, indicates vehicle according to number 1,5,2,6,3,4
Sequence is parked；
(6) contemporary individual adaptation degree is resolved, saves optimum individual as elite individual；
Related fitness are as follows: selection deck nonavailability is fitness function；
(7) judge whether that reaching maximum number of iterations or average fitness reaches desired value, if it is goes to step
(11), step (8) are otherwise gone to；
(8) all individuals are with the difference of worst individual adaptation degree as all new fitness of individual；
(9) hereditary selection, intersection and variation are carried out, population of new generation is generated；
Related selection operation is chosen individual progress genetic manipulation from parent using roulette wheel selection and is entered next
In generation, if amphibious vehicle quantity is n, the fitness size of i-th vehicle is fi, then this vehicle is selected probability PiAre as follows:
Related crossover operation avoids coding from repeating using sequence crossover method, it is assumed that two father's individual intersection processes are such as
Under:
Firstly, the cross section on first father's chromosome of random selection,
Secondly, by gene identical with first chromosome on second father's chromosome remove, and by remaining gene according to
Sequence arrangement originally,
Again, by the cross section of the same first father's chromosome of the remainder of second father's chromosome according to original sequence
Daughter chromosome is spliced into,
Finally, making to obtain second daughter chromosome in the same way；
Related mutation operation are as follows: for random chromosome, randomly select two different genes on chromosome
It swaps；
(10) elite individual replaces the worst individual of population of new generation, goes to step (6)；
(11) optimum individual in last generation population is decoded, obtains the optimal ordering of vehicle Boulez；
(12) amphibious vehicle cloth column position is determined using level of subsistence location algorithm；
(13) amphibious vehicle Boulez is completed.
By taking the U.S. " wasp grade " amphibious assault ship as an example.The length of deck cloth column space is 100 meters, width is 20 meters.Ginseng
There are A type, Type B with the vehicle of Boulez, four kinds of vehicles of c-type and D type consider the expanded dimension between vehicle after distance are as follows: A type is long
6.40m and width 2.50m, the long 11.00m of Type B and width 3.00m, the long 9.77m of c-type and width 3.66m, the long 5.00m of D type and width 4.00m.
If four kinds of vehicle models maximum cloth number of columns are 80, number in order, i.e. A is 1-80, and B 81-160, C 161-240, D are
241-320。
Compare the simulation result of traditional genetic algorithm, simulated annealing and adaptive elite genetic algorithm.Two kinds of setting
The initial parameter of genetic algorithm: the number of iterations 100 times, Population Size 100, crossover probability 0.9, mutation probability 0.15.Mould is set
The initial parameter of quasi- annealing algorithm: 2000 degree of initial temperature, terminate 1 degree of temperature, the number of iterations 1000 times at each temperature, drop
Warm coefficient 0.95.
The amphibious vehicle Boulez figure of traditional genetic algorithm, simulated annealing and adaptive elite genetic algorithm is respectively as schemed
Shown in 2-4.Three kinds of optimization algorithms realize the automatic Boulez of amphibious vehicle, obtain respective optimal Boulez result.Among Fig. 2 and scheme
The all obvious appearance one in 3 right sides is long and narrow not to utilize deck space.Fig. 4 does not occur not utilizing space significantly.
The fitness curve of traditional genetic algorithm, simulated annealing and adaptive elite genetic algorithm is as illustrated in figs. 5-7.
In fig. 5-7, traditional genetic algorithm fitness curve is begun to decline slowly after the 10th generation, and fitness instead of changes afterwards 10
It is unobvious.Simulated annealing obtains a more outstanding solution in the 75th generation outer circulation.Adaptive elite genetic algorithm exists
Fitness variation is unobvious after 20th generation, and fitness decline is slow.Theoretically the number of iterations is more, and the result of algorithm is more excellent
Show, but will increase dramatically calculation amount.Simulated annealing is compared with two kinds of genetic algorithms, and deck nonavailability is higher, Boulez
As a result poor, calculate time longest.The shortcomings that simulated annealing first is that Initial parameter sets are complicated, the solution of problem is produced
It is raw to influence.Two kinds of genetic algorithms can obtain optimization performance more better than simulated annealing in first time setting initial parameter.
The deck utilization rate of traditional genetic algorithm, simulated annealing and adaptive elite genetic algorithm is respectively
95.90%, 95.28% and 97.44%, calculating the time is respectively 140.07s, 295.29s and 136.5s, Boulez A type, Type B, C
Type and D type amphibious vehicle quantity are respectively (56,21,7,4), (61,18,9,1) and (15,18,20,20).Adaptive elite loses
The deck utilization rate of propagation algorithm improves 1.61% than the deck utilization rate of traditional genetic algorithm, than the deck for simulating degeneration algorithm
Utilization rate improves 2.27%.The optimization time of adaptive elite genetic algorithm compared with remaining two kinds of optimization algorithm, when optimization
Between it is most short.The Boulez vehicle fleet size of three kinds of algorithms is respectively 88,89 and 73.The cloth number of columns of adaptive elite genetic algorithm is most
It is few, this is because optimization aim is that deck nonavailability is minimum, rather than cloth number of columns is most.Adaptive elite genetic algorithm
Every kind of vehicle cloth number of columns is closer to, and can satisfy actual load demand.And the cloth number of columns of other two kinds of optimization algorithms point
Cloth is uneven, is concentrated mainly on A type vehicle, both optimum results are not inconsistent with actual demand.
In conclusion adaptive elite genetic algorithm is saved the optimum individual of every generation using elitism strategy, and
The worst individual in population is replaced after genetic manipulation, can guarantee that optimal individual will not be destroyed in this way.It uses simultaneously
Adaptively selected strategy, by in population minimum fitness make it is poor so that the fitness of population with the change of environment and
Change, improve the adaptability of population, so that fitness is differed lesser individual and distinguished in the selection process, be can be improved
The outstanding degree of solution.
Claims (1)
1. a kind of amphibious vehicle Boulez optimization method based on adaptive elite genetic algorithm, which is characterized in that including walking as follows
It is rapid:
(1) amphibious vehicle and Boulez bulk are obtained；
Related amphibious vehicle and Boulez bulk are as follows: the cloth column space of vehicle hold rectangle is P, and a length of L, width W are deposited
In n vehicle { Pi, i=1...n }, length and width is respectively liAnd wi, in the plan view from above of vehicle hold deck, if the lower left corner
For origin O (0,0), the upper left corner is (0, L), and the lower right corner is (W, 0), rectangle vehicle PiTop left corner apex be (xi1,yi1), then Pi
Bottom right angular coordinate is
(2) clear amphibious vehicle Boulez constraint condition；
Related constraint condition are as follows: two vehicle PiAnd Pj(i ≠ j) is not overlapped, and vehicle cannot be placed on except cloth column space,
The height of vehicle and width are greater than 0 simultaneously, and every kind of vehicle can all have the limitation of maximum quantity, numrIt is r type vehicle Boulez
Quantity, NrIt is the maximum quantity of r kind vehicle, constrains as follows:
(3) amphibious vehicle Boulez objective function is determined；
Related objective function is that vehicle hold deck nonavailability is minimum, i.e. the sum of Boulez area maximum shared by vehicle, is indicated
Are as follows:
(4) adaptive elite genetic algorithm initial parameter is set；
Related initial parameter are as follows: the number of iterations is 100 times, Population Size 100, crossover probability 0.9, and mutation probability is
0.15；
(5) first generation amphibious vehicle Boulez kind group coding is randomly generated；
Related population generates are as follows: the mode for generating initial population is the corresponding group of individuals of chromosome constituted using random number
At initial population, amphibious vehicle Boulez problem can be converted into the combinatorial optimization problem of vehicle parking sequence, choose decimal system vehicle
Number is coding mode；
(6) contemporary individual adaptation degree is resolved, saves optimum individual as elite individual；
Related fitness are as follows: selection deck nonavailability is fitness function；
(7) judge whether that reaching maximum number of iterations or average fitness reaches desired value, if it is goes to step (11), it is no
Then go to step (8)；
(8) all individuals are with the difference of worst individual adaptation degree as all new fitness of individual；
(9) hereditary selection, intersection and variation are carried out, population of new generation is generated；
Related selection operation uses roulette wheel selection to choose individual progress genetic manipulation from parent and enters the next generation, if
Amphibious vehicle quantity is n, and the fitness size of i-th vehicle is fi, then this vehicle is selected probability PiAre as follows:
Related crossover operation avoids coding from repeating using sequence crossover method, it is assumed that two father's individual intersection processes are as follows:
Firstly, the cross section on first father's chromosome of random selection,
Secondly, gene identical with first chromosome on second father's chromosome is removed, and by remaining gene according to original
Sequence arrangement,
Again, by the cross section of the same first father's chromosome of the remainder of second father's chromosome according to original sequential concatenation
At daughter chromosome,
Finally, making to obtain second daughter chromosome in the same way；
Related mutation operation are as follows: for random chromosome, the two different genes randomly selected on chromosome are carried out
Exchange；
(10) elite individual replaces the worst individual of population of new generation, goes to step (6)；
(11) optimum individual in last generation population is decoded, obtains the optimal ordering of vehicle Boulez；
(12) amphibious vehicle cloth column position is determined using level of subsistence location algorithm；
(13) amphibious vehicle Boulez is completed.
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| CN111291969A (en) * | 2020-01-14 | 2020-06-16 | 东南大学 | Automobile reordering method based on genetic algorithm |
| CN111461402A (en) * | 2020-03-06 | 2020-07-28 | 上海汽车集团股份有限公司 | Logistics schedule optimization method and device, computer readable storage medium and terminal |
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| CN112418528A (en) * | 2020-11-24 | 2021-02-26 | 哈尔滨理工大学 | Amphibious vehicle layout area utilization maximization method based on multi-strategy dynamic adjustment |
| CN113222272A (en) * | 2021-05-26 | 2021-08-06 | 合肥工业大学 | Emergency material transportation and loading cooperative optimization method based on double-layer genetic coding |
| CN113222272B (en) * | 2021-05-26 | 2022-09-20 | 合肥工业大学 | Emergency material transportation and loading cooperative optimization method based on double-layer genetic coding |
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