CN110032902B - Reader anti-collision method and device based on single parent genetic algorithm - Google Patents
Reader anti-collision method and device based on single parent genetic algorithm Download PDFInfo
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Abstract
The invention discloses a reader anti-collision method and device based on a single parent genetic algorithm. The method comprises the steps that a server side obtains chromosome fitness of a child population, after annealing and stretching are carried out on the fitness of chromosomes, a plurality of chromosomes are randomly selected as parent chromosomes, self-crossing operation is carried out on the parent chromosomes in the parent population to accelerate convergence, the fact that the solution of the chromosomes obtained in the process of obtaining the maximum chromosomes in an iteration mode is kept within a boundary range is effectively guaranteed, meanwhile, convergence speed and convergence accuracy of an algorithm are greatly increased after self-crossing operation is introduced, stretching and amplifying of the chromosomes enable excellent chromosomes to be selected more probably, and therefore a more accurate and efficient reader distribution scheme is obtained.
Description
Technical Field
The invention relates to the field of communication, in particular to a reader anti-collision method and a reader anti-collision device based on a single parent genetic algorithm.
Background
In an application system of a radio frequency identification technology (RFID), a reader is required to identify and read an electronic tag, and when a plurality of readers work simultaneously in the same area, mutual collision of signals of the readers is easy to occur, so that the electronic tag cannot correctly decode the signals from the readers. The anti-collision of the reader is realized, the reader resources are essentially reasonably distributed, the reader resources are mostly distributed by using a genetic algorithm in the existing scheme, in the genetic algorithm, a population chromosome is usually adopted to express the distribution scheme of all time slot reader resources, and each gene in the optimal solution of the chromosome is the optimal distribution scheme of the reader resources. However, in the process of obtaining the optimal solution of the chromosome according to the existing genetic algorithm, the chromosome is easily caused to exceed the boundary range, so that the resource allocation scheme cannot be obtained.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a reader anti-collision method, a reader anti-collision device, reader anti-collision equipment and a reader anti-collision storage medium based on a single parent genetic algorithm, which can ensure that a resource allocation scheme is obtained within a boundary range during iterative computation in practical application, and improve the efficiency of allocating reader resources.
The technical scheme adopted by the invention for solving the problems is as follows: in a first aspect, the invention provides a reader anti-collision method based on a single parent genetic algorithm, which comprises the following steps:
the method comprises the steps that a server side obtains reader resources, integer coding is carried out on the reader resources, an initial population is generated, and the initial population is set as a child population;
after annealing and stretching the chromosomes of the offspring population by the server, randomly selecting a plurality of chromosomes and setting the chromosomes as parent chromosomes, performing self-crossing operation on the parent chromosomes to form a parent population, setting the parent population as the offspring population, and iteratively executing the operation of the step;
and when the server finishes the preset iteration times, acquiring the maximum chromosome in the offspring population obtained by the last iteration as a distribution scheme of the reader resource.
Further, the annealing and stretching of the chromosomes of the offspring population by the service end specifically comprises the following steps:
the server side obtains a first fitness of a chromosome of the offspring population;
the server ranks the chromosomes of the offspring population according to the first fitness, and sets a rank value obtained by ranking as a second fitness of the chromosomes of the offspring population;
and the service end carries out annealing stretching on the second fitness.
Further, the first fitness of the initial population is an initial tag identification number corresponding to each chromosome.
Further, the server randomly selects a plurality of chromosomes as parent chromosomes according to a roulette algorithm.
Further, the performing the self-crossing operation on the parent chromosome further comprises: and the server performs mutation operation and selection operation on the parent population.
Further, after the service end performs mutation operation and selection operation on the parent population, the method further comprises the following steps:
the server side obtains the average fitness of the offspring population and the average fitness of the parent population;
and when the average fitness of the parent is less than or equal to the average fitness of the child, performing inhibition operation and supplement operation on the parent population.
In a second aspect, the present invention provides a reader collision avoidance device based on a single parent genetic algorithm, including a CPU unit, where the CPU unit is configured to execute the following steps:
the method comprises the steps that a server side obtains reader resources, integer coding is carried out on the reader resources, an initial population is generated, and the initial population is set as a child population;
after annealing and stretching the chromosomes of the offspring population by the server, randomly selecting a plurality of chromosomes and setting the chromosomes as parent chromosomes, performing self-crossing operation on the parent chromosomes to form a parent population, setting the parent population as the offspring population, and iteratively executing the operation of the step;
and when the server finishes the preset iteration times, acquiring the maximum chromosome in the offspring population obtained by the last iteration as a distribution scheme of the reader resource.
Further, the CPU unit is further configured to perform the steps of:
the server side obtains a first fitness of a chromosome of the offspring population;
the server ranks the chromosomes of the offspring population according to the first fitness, and sets a rank value obtained by ranking as a second fitness of the chromosomes of the offspring population;
and the service end carries out annealing stretching on the second fitness.
Further, the CPU unit is further configured to perform the steps of:
the server side obtains the average fitness of the offspring population and the average fitness of the parent population;
and when the average fitness of the parent is less than or equal to the average fitness of the child, performing inhibition operation and supplement operation on the parent population.
In a third aspect, the invention provides a reader collision avoidance device based on a single parent genetic algorithm, which comprises at least one control processor and a memory, wherein the memory is in communication connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the reader collision avoidance method based on the single parent genetic algorithm as described above.
In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the reader collision avoidance method based on the single parent genetic algorithm as described above.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program stored on a computer-readable storage medium, the computer program comprising program instructions that, when executed by a computer, cause the computer to perform the method for reader collision avoidance based on the single parent genetic algorithm as described above.
One or more technical schemes provided in the embodiment of the invention have at least the following beneficial effects: the invention adopts a reader anti-collision method and a reader anti-collision device based on a single parent genetic algorithm. After the chromosome is annealed and stretched by the server side to the offspring population, a plurality of chromosomes are randomly selected as parent chromosomes, self-crossing operation is performed on the parent chromosomes in the parent population to accelerate convergence, so that compared with the prior art, the method and the device effectively ensure that the solution of the chromosome obtained in the process of iteratively obtaining the maximum chromosome is kept in the boundary range, the convergence speed and the convergence precision of the algorithm are greatly increased after the self-crossing operation is introduced, the excellent chromosomes can be selected more probably by stretching and amplifying the chromosomes, and a more accurate and efficient reader distribution scheme is obtained.
Drawings
The invention is further illustrated with reference to the following figures and examples.
Fig. 1 is a flowchart of a reader anti-collision method based on a single parent genetic algorithm according to an embodiment of the present invention;
fig. 2 is a flowchart of annealing and stretching in a reader anti-collision method based on a single parent genetic algorithm according to an embodiment of the present invention;
fig. 3 is a flowchart after mutation operations and selection operations are performed on a parent population in a reader collision avoidance method based on a single parent genetic algorithm according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating self-intersection operations performed on parent chromosomes in a reader collision avoidance method based on a single-parent genetic algorithm according to an embodiment of the present invention;
fig. 5 is a complete flowchart of a reader anti-collision method based on a single parent genetic algorithm according to an embodiment of the present invention;
fig. 6 is a schematic diagram of an apparatus for preventing collision of readers based on a single parent genetic algorithm according to a second embodiment of the present invention.
Detailed Description
At present, in an application system of a radio frequency identification technology (RFID), a reader is required to be used for identifying and reading an electronic tag, and when a plurality of readers work simultaneously in the same area, mutual collision of signals of the readers is easy to occur, so that the electronic tag cannot correctly decode the signals from the readers. The anti-collision of the reader is realized, the reader resources are essentially reasonably distributed, the reader resources are mostly distributed by using a genetic algorithm in the existing scheme, in the genetic algorithm, a population chromosome is usually adopted to express the distribution scheme of all time slot reader resources, and each gene in the optimal solution of the chromosome is the optimal distribution scheme of the reader resources. However, in the process of obtaining the optimal solution of the chromosome according to the existing genetic algorithm, the crossover operation is performed between different chromosomes, so that the original solution is easily damaged, and the chromosome exceeds the boundary range, thereby causing that the resource allocation scheme cannot be obtained.
Based on the method, the reader anti-collision method and the reader anti-collision device based on the single parent genetic algorithm are adopted. After the chromosome is annealed and stretched by the server side to the offspring population, a plurality of chromosomes are randomly selected as parent chromosomes, self-crossing operation is performed on the parent chromosomes in the parent population to accelerate convergence, so that compared with the prior art, the method and the device effectively ensure that the solution of the chromosome obtained in the process of iteratively obtaining the maximum chromosome is kept in the boundary range, the convergence speed and the convergence precision of the algorithm are greatly increased after the self-crossing operation is introduced, the excellent chromosomes can be selected more probably by stretching and amplifying the chromosomes, and a more accurate and efficient reader distribution scheme is obtained.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, if not conflicted, the various features of the embodiments of the invention may be combined with each other within the scope of protection of the invention. Additionally, while functional block divisions are performed in apparatus schematics, with logical sequences shown in flowcharts, in some cases, steps shown or described may be performed in sequences other than block divisions in apparatus or flowcharts.
Referring to fig. 1, the invention provides a reader anti-collision method based on a single parent genetic algorithm, which comprises the following steps:
step S110, the server side obtains reader resources, performs integer coding on the reader resources to generate an initial population, and sets the initial population as a child population;
step S120, after annealing and stretching the chromosomes of the offspring population by the server, randomly selecting a plurality of chromosomes and setting the chromosomes as parent chromosomes, performing self-crossing operation on the parent chromosomes to form a parent population, setting the parent population as the offspring population, and iteratively executing the operation of the step;
and S130, when the server finishes the preset iteration times, acquiring the maximum chromosome in the offspring population obtained by the last iteration as a distribution scheme of the reader resource.
In step S120 of this embodiment, any operator, such as a selection operator, a crossover operator, and an annealing operator, may be selected for the processing of the chromosomes of the sub-generation population, and in this embodiment, the annealing operator is preferably adopted to stretch the fitness of the mature chromosomes. After the chromosomes in the offspring population are obtained, as most of the chromosomes are not mature, in order to avoid overlarge calculation amount, the fitness is preferably compressed during calculation so as to improve the calculation efficiency; and for excellent chromosomes, the fitness is usually higher, so that the fitness of mature chromosomes is stretched and amplified through an annealing operator after calculation, the probability of selecting the excellent chromosomes can be improved, and the reasonability of reader resource allocation is improved.
Referring to fig. 4, in the present embodiment, a self-crossing operation is preferably performed in the parent chromosome 1. As shown in fig. 4, a time slot 420 is randomly selected from the time slots included in the parent chromosome 410, 2 genes are randomly selected from the selected time slot 420, and the values of the selected genes are exchanged, that is, 2 readers are selected and the operating frequencies thereof are exchanged. The self-crossing operation is combined with the annealing algorithm, so that the frequency difference between the readers can be increased under the condition of accelerating algorithm convergence, the convergence speed and the convergence precision are improved, and the optimal reader distribution scheme is obtained within the boundary range.
In step S130 of this embodiment, the iteration number may be obtained in any manner, and in this embodiment, it is preferably preset in the server, and the counting is performed once every iteration, and the iteration is stopped when the counted value is equal to the preset iteration number.
In step S130 of this embodiment, after the iteration is completed, the largest chromosome may be selected from any child population as the reader resource allocation scheme, and this embodiment preferably selects the largest chromosome from the child population obtained by the last iteration. In the iteration process, a plurality of child populations appear, the later child populations have more times of self-crossing and other operations, so that the obtained chromosomes are mature, namely, the reader resource allocation scheme is more reasonable, the largest chromosome is selected from the child populations obtained in the last iteration, and the obtained reader resource allocation scheme can be ensured to be most reasonable.
In this embodiment, preferably, the chromosomes in the initial population are generated by randomly allocating time slots and readers, so that the reader resource allocation scheme obtained after iterative computation is more stable.
Referring to fig. 2, further, in another embodiment of the present invention, annealing and stretching the chromosomes of the offspring population by the service end specifically includes the following steps:
step S211, the server side obtains a first fitness of chromosomes of the offspring population;
step S212, the server ranks the chromosomes of the offspring population according to the first fitness, and sets a rank value obtained by ranking as a second fitness of the chromosomes of the offspring population;
and S213, annealing and stretching the second fitness by the service end.
In this embodiment, when the sub-population is the initial population, the first fitness is the initial tag identification number of the reader, and the tag identification numbers are preferably arranged from small to large during sorting, so that the sorted sequence value can represent the tag identification number of the chromosome.
In step S213 of this embodiment, for the population with the population size N, the annealing and stretching are performed according to the following formula:
wherein f (i) is the i-th chromosome after sorting, i is the [1, N ]](ii) a K is the algebraic number of iterations, e.g. 4 iterations have been completed, K equals 4, T0Is the initial temperature.
Further, in another embodiment of the present invention, the first fitness of the initial population is the initial tag identification number corresponding to each chromosome.
In this embodiment, the fitness of the chromosomes of the initial population may be an initial ranking order value, or may be a tag identification number corresponding to each chromosome. In the embodiment, the identification number of the tags is preselected, so that when the chromosomes are sorted according to the fitness of the chromosomes, the chromosomes with a large identification number of transitions can be sorted to a later position, so that a larger sequence value is obtained, and the probability of selecting excellent chromosomes is increased.
Further, in another embodiment of the invention, the server randomly selects a plurality of chromosomes as parent chromosomes according to a roulette algorithm.
In this embodiment, any algorithm may be adopted when randomly selecting chromosomes, and a roulette algorithm is preferred in this embodiment, which is beneficial to realize that chromosomes can be selected repeatedly, and ensure that excellent chromosomes can be selected during iteration.
Further, in another embodiment of the present invention, the self-crossing operation performed on the parent chromosome further comprises: and the server performs mutation operation and selection operation on the parent population.
In this embodiment, any operation may be performed after the generation of the parent chromosome, and in this embodiment, it is preferable to perform the mutation operation and the selection operation on the parent chromosome after the self-crossing. And the mutation operation is to randomly select a gene position in the chromosome, if the time slot to which the selected gene position belongs has other readers working, remove the used frequency bands from the available frequency band resources, then randomly select a frequency band from the removed and updated available frequency bands to replace the value on the selected gene position, and if the available frequency band becomes empty, reselect a time slot for mutation.
In this embodiment, it is preferable to perform the selection operation after the mutation operation, that is, after the mutation is completed, calculating the fitness of the new chromosome after the mutation, and replacing the parent chromosome with the new chromosome if the fitness of the new chromosome is greater than that of the parent chromosome.
Referring to fig. 3, further, in another embodiment of the present invention, the step of performing mutation operation and selection operation on the parent population by the service end further comprises:
step S221, the server side obtains the average fitness of the offspring population and the average fitness of the parent population;
and step S222, when the average fitness of the parent is smaller than or equal to the average fitness of the child, performing suppression operation and supplement operation on the parent population.
In this embodiment, preferably, the average fitness of the parent population is evaluated in steps S221 and S222, that is, the average fitness of the parents and the average fitness of the offspring are compared, if the average fitness of the parents is not improved after the self-intersection operation, the mutation operation and the selection operation, that is, the fitness of the selected chromosome is poor, at this time, the chromosome with poor fitness is eliminated by the suppression operation, and the quality of the chromosome can be improved.
In the present embodiment, after the suppression operation is performed on the parent population, in order to ensure that the number of chromosomes is not changed, chromosomes with the same number as that of the eliminated chromosomes are randomly generated for further iteration.
Referring to fig. 5, in addition, another embodiment of the present invention provides a reader collision avoidance method based on a single parent genetic algorithm, including the following steps:
step S5110, the server side obtains reader resources, performs integer coding on the reader resources, randomly generates an initial population, and sets the initial population as a child population;
step S5210, the server side obtains offspring chromosomes in the offspring population, obtains first fitness of the offspring chromosomes, sorts the chromosomes from small to large according to the first fitness, and takes the sorted sequence value as second fitness of the offspring chromosomes;
step S5220, the server stretches the second fitness through an annealing operator, randomly selects a plurality of chromosomes from the offspring through a roulette algorithm, and sets the chromosomes as parent chromosomes;
step S5230, after the service end sequentially executes self-crossing operation, mutation operation and selection operation on the parent chromosomes, a parent population is formed according to the parent chromosomes;
step S5240, acquiring the parent average fitness of the parent population and the offspring average fitness of the offspring population; if the average fitness of the parent is greater than the average fitness of the children, step S5310 is executed, otherwise step 5250 is executed
Step S5250, after the inhibition operation and the supplement operation are executed on the parent population, step S5310 is executed;
step S5310, the server side obtains the current iteration times, if the current iteration times do not reach the preset iteration times, the parent population in the step S5240 is set as a child population, and the step S5210-step S5240 are executed in an iterative manner; if the preset iteration number is reached, executing step S5410;
and step S5410, acquiring the maximum chromosome after the iteration is finished as an optimal resource allocation scheme.
In the embodiment, a reader anti-collision method based on a single parent genetic algorithm is adopted. After the chromosome is annealed and stretched by the server side to the offspring population, a plurality of chromosomes are randomly selected as parent chromosomes, self-crossing operation accelerated convergence is performed on the parent chromosomes in the parent population, the chromosome solution obtained in the process of iteratively obtaining the maximum chromosome is effectively ensured to be kept in the boundary range, meanwhile, the convergence speed and the convergence precision of the algorithm are greatly increased after the self-crossing operation is introduced, the excellent chromosomes can be selected more probably by stretching and amplifying the chromosomes, and therefore a more accurate and efficient reader distribution scheme is obtained
Referring to fig. 6, a second embodiment of the present invention further provides a reader anti-collision device based on a single parent genetic algorithm, where the device is an intelligent device, such as a smart phone, a computer, a tablet computer, and the like, the device is a device directly connected to a reader and capable of sending a resource allocation scheme to the reader, and is not a third-party device between the two devices, and the embodiment is described by taking a computer as an example:
in the computer 6000 for executing the reader collision avoidance method based on the single parent genetic algorithm, the CPU unit 6100 is included, and the CPU unit 6100 is configured to perform the steps of:
the server side obtains the reader resources, performs integer coding on the reader resources to generate an initial population, and sets the initial population as a child population;
after annealing and stretching the chromosomes of the offspring population by the server, randomly selecting a plurality of chromosomes and setting the chromosomes as parent chromosomes, performing self-crossing operation on the parent chromosomes to form a parent population, setting the parent population as the offspring population, and iteratively executing the operation of the step;
and when the server finishes the preset iteration times, acquiring the maximum chromosome in the offspring population obtained by the last iteration as a distribution scheme of the reader resource.
In this embodiment, a server for executing the reader anti-collision method based on the single parent genetic algorithm is installed in the intelligent device, and the reader anti-collision method based on the single parent genetic algorithm is not required to be completed by user operation in this embodiment, but is automatically completed by the CPU 6100 when the computer 6000 is started.
Further, the CPU 6100 is also configured to perform the following steps:
the server side obtains a first fitness of a chromosome of the offspring population;
the server ranks the chromosomes of the offspring population according to the first fitness, and sets a rank value obtained by ranking as a second fitness of the chromosomes of the offspring population;
and the service end carries out annealing stretching on the second fitness.
Further, the CPU 6100 is also configured to perform the following steps:
the server side obtains the average fitness of the filial generation population and the average fitness of the parent generation population;
and when the average fitness of the parent is less than or equal to the average fitness of the child, performing inhibition operation and supplement operation on the parent population.
The computer 6000 and the CPU 6100 may be connected through a bus or other means, and the computer 6000 further includes a memory as a non-transitory computer readable storage medium, which may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the apparatus for executing the reader collision avoidance method based on the single parent genetic algorithm according to the embodiment of the present invention. The computer 6000 controls the CPU 6100 to execute various functional applications and data processing for executing the reader collision prevention method based on the monaural genetic algorithm by running the non-transitory software programs, instructions, and modules stored in the memory, that is, to implement the reader collision prevention method based on the monaural genetic algorithm of the above-described method embodiments.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the CPU unit 6100, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the CPU 6100, which may be connected to the computer 6000 through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory, and when executed by the CPU unit 6100, perform the reader collision avoidance method based on the single parent genetic algorithm in the above-described method embodiments.
In addition, the third embodiment of the present invention further provides a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and the computer-executable instructions are executed by the CPU 6100, so as to implement the reader anti-collision method based on the single-parent genetic algorithm described above.
The above-described apparatus embodiments are merely illustrative, and the apparatuses illustrated as separate components may or may not be physically separate, may be located in one place, or may be distributed over a plurality of network apparatuses. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
It should be noted that, since the apparatus for executing the reader anti-collision method based on the monaural genetic algorithm in this embodiment is based on the same inventive concept as the reader anti-collision connection method based on the monaural genetic algorithm described above, the corresponding contents in the method embodiment are also applicable to this apparatus embodiment, and are not described in detail here.
Through the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by software plus a general hardware platform. Those skilled in the art will appreciate that all or part of the processes in the methods for implementing the embodiments described above can be implemented by hardware related to instructions of a computer program, and the program can be stored in a computer readable storage medium, and when executed, can include the processes in the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
While the preferred embodiments of the present invention have been described in detail, it will be understood by those skilled in the art that the foregoing and various other changes, omissions and deviations in the form and detail thereof may be made without departing from the scope of this invention.
Claims (7)
1. A reader anti-collision method based on a single parent genetic algorithm is characterized by comprising the following steps:
the method comprises the steps that a server side obtains reader resources, integer coding is carried out on the reader resources, an initial population is generated, and the initial population is set as a child population;
after annealing and stretching the chromosomes of the offspring population by the server, randomly selecting a plurality of chromosomes and setting the chromosomes as parent chromosomes, performing self-crossing operation on the parent chromosomes to form a parent population, setting the parent population as the offspring population, and iteratively executing the operation of the step;
when the server side finishes the preset iteration times, acquiring the maximum chromosome in the offspring population obtained by the last iteration as a distribution scheme of reader resources;
the annealing and stretching of the chromosomes of the offspring population by the server specifically comprises the following steps:
the server side obtains a first fitness of a chromosome of the offspring population; wherein the first fitness of the initial population is the identification number of the initial label corresponding to each chromosome;
the server-side sorts the chromosomes of the offspring population from small to large according to the first fitness, and sets a sequence value obtained by sorting as a second fitness of the chromosomes of the offspring population;
and the service end carries out annealing stretching on the second fitness.
2. The reader anti-collision method based on the single parent genetic algorithm, according to claim 1, is characterized in that: and the server side selects a parent chromosome from the child population according to a roulette algorithm.
3. The method for reader collision avoidance based on the single-parent genetic algorithm according to claim 1, wherein the performing the self-crossing operation on the parent chromosome further comprises: and the server performs mutation operation and selection operation on the parent population.
4. The reader anti-collision method based on the single-parent genetic algorithm, according to claim 3, after the server performs mutation operation and selection operation on the parent population, the method further comprises the following steps:
the server side obtains the average fitness of the offspring population and the average fitness of the parent population;
and when the average fitness of the parent is less than or equal to the average fitness of the child, performing inhibition operation and supplement operation on the parent population.
5. The reader anti-collision device based on the single parent genetic algorithm is characterized by comprising a CPU (central processing unit), wherein the CPU is used for executing the following steps:
the method comprises the steps that a server side obtains reader resources, integer coding is carried out on the reader resources, an initial population is generated, and the initial population is set as a child population;
after annealing and stretching the chromosomes of the offspring population by the server, randomly selecting a plurality of chromosomes and setting the chromosomes as parent chromosomes, performing self-crossing operation on the parent chromosomes to form a parent population, setting the parent population as the offspring population, and iteratively executing the operation of the step;
when the server side finishes the preset iteration times, acquiring the maximum chromosome in the offspring population obtained by the last iteration as a distribution scheme of reader resources;
the server side obtains a first fitness of a chromosome of the offspring population; wherein the first fitness of the initial population is the identification number of the initial label corresponding to each chromosome;
the server-side sorts the chromosomes of the offspring population from small to large according to the first fitness, and sets a sequence value obtained by sorting as a second fitness of the chromosomes of the offspring population;
and the service end carries out annealing stretching on the second fitness.
6. The reader collision avoidance device based on the single parent genetic algorithm according to claim 5, wherein the CPU unit is further configured to execute the following steps:
the server side obtains the average fitness of the offspring population and the average fitness of the parent population;
and when the average fitness of the parent is less than or equal to the average fitness of the child, performing inhibition operation and supplement operation on the parent population.
7. A computer-readable storage medium characterized by: the computer-readable storage medium stores computer-executable instructions for causing a computer to perform a method for reader collision avoidance based on a single parent genetic algorithm as claimed in any one of claims 1 to 4.
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