CN117291364A - Layout planning method, device, equipment and storage medium - Google Patents
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Abstract
The embodiment of the application provides a layout planning method, a layout planning device, electronic equipment and a computer storage medium. The method comprises the following steps: acquiring initial position information, layout attribute information and position constraint information among target areas to be laid out; performing coding operation on the initial position information and the layout attribute information of each target area to obtain an initial population containing a plurality of individuals; wherein one individual corresponds to one layout scheme; calculating the fitness of each individual in the initial population; the fitness of the individual represents the violation degree of the layout scheme corresponding to the individual on the position constraint information; obtaining target individuals by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; and obtaining a target layout scheme according to the target individual. According to the embodiment of the application, the rationality of the layout scheme can be improved while the layout planning efficiency is improved.
Description
Technical Field
The embodiment of the application relates to the technical field of industrial production, in particular to a layout planning method, a layout planning device, electronic equipment and a computer storage medium.
Background
Layout planning mainly refers to planning specific layout positions of a plurality of target areas to be deployed in a target space. Taking a factory as an example, a factory building typically requires the deployment of a number of different process areas, or a number of different equipment areas. The factory layout rules are used for planning specific positions of a plurality of process areas or equipment areas to be deployed in the factory building so as to reduce the material flow of material handling between different process areas or equipment areas.
In the prior art, planning and layout are usually performed by a designer according to own experience. However, since the number of target areas is generally large, and there may be a certain position constraint between different target areas, the above layout planning method by means of manual implementation is inefficient and the obtained result is generally not ideal.
Disclosure of Invention
In view of this, one of the technical problems to be solved in the embodiments of the present application is to provide a layout planning method, a device, an electronic apparatus and a storage medium for determining a layout plan, which improves the rationality of the layout plan while improving the layout planning efficiency.
In a first aspect, an embodiment of the present application provides a layout planning method, where the method includes:
acquiring initial position information, layout attribute information and position constraint information among target areas to be laid out; the layout attribute information comprises rotation information and/or candidate size information of each target area;
performing coding operation on the initial position information and the layout attribute information of each target area to obtain an initial population containing a plurality of individuals; wherein one individual corresponds to one layout scheme;
calculating the fitness of each individual in the initial population; the fitness of the individual represents the violation degree of the layout scheme corresponding to the individual on the position constraint information;
obtaining target individuals by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; and obtaining a target layout scheme according to the target individual.
In a second aspect, an embodiment of the present application provides a layout planning apparatus, including:
the information acquisition module is used for acquiring initial position information, layout attribute information and position constraint information among the target areas to be laid out; the layout attribute information comprises rotation information and/or candidate size information of each target area;
the coding module is used for carrying out coding operation on the initial position information and the layout attribute information of each target area to obtain an initial population containing a plurality of individuals; wherein one individual corresponds to one layout scheme;
the calculating module is used for calculating the fitness of each individual in the initial population; the fitness of the individual represents the violation degree of the layout scheme corresponding to the individual on the position constraint information;
the scheme obtaining module is used for obtaining target individuals by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; and obtaining a target layout scheme according to the target individual.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the memory, and the communication interface complete communication with each other through the communication bus; the memory is used for storing a computer program, and the processor is used for implementing the layout planning method according to the first aspect when executing the program stored on the memory.
In a fourth aspect, embodiments of the present application provide a computer storage medium having a computer program stored thereon, which when executed by a processor implements a layout planning method as described in the first aspect or any one of the embodiments of the first aspect.
The embodiment of the application provides a layout planning method, a layout planning device, electronic equipment and a computer storage medium. According to the embodiment of the application, the layout scheme is converted into individuals in the population by encoding the layout attribute information of each target area; the degree of violation of the layout scheme on the position constraint is calculated, so that the individual fitness is obtained; thereby converting the layout planning problem into an optimized search problem which can be solved by a genetic algorithm to obtain a target layout scheme. Therefore, the layout planning method and device can improve the rationality of the layout scheme while improving the layout planning efficiency.
In addition, in the embodiment of the application, when individuals in the initial population are constructed to search for the target layout scheme by adopting a genetic algorithm, not only the position change of each target area is considered, but also layout attribute information such as gesture rotation and/or size change which may exist in the layout process of each target area is considered; in addition, when generating the individual evaluation index (fitness), the position constraint condition existing between the target areas is also considered. Therefore, through the layout planning scheme provided by the embodiment of the application, a more reasonable layout scheme can be obtained.
Drawings
Some specific embodiments of the present application will be described in detail below by way of example and not by way of limitation with reference to the accompanying drawings. The same reference numbers will be used throughout the drawings to refer to the same or like parts or portions. It will be appreciated by those skilled in the art that the drawings are not necessarily drawn to scale. In the accompanying drawings:
fig. 1 is a flow chart of a layout planning method according to an embodiment of the present application;
FIG. 2 is a schematic view of a position constraint in an embodiment of the present application;
FIG. 3 is a schematic structural diagram of an individual according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of steps in a layout planning process according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a layout planning apparatus according to an embodiment of the present application.
List of reference numerals:
101: acquiring initial position information, layout attribute information and position constraint information among target areas to be laid out; wherein the layout attribute information includes rotation information and/or candidate size information of the target area;
102: performing coding operation on the initial position information and the layout attribute information of each target area to obtain an initial population containing a plurality of individuals; wherein one individual corresponds to one layout scheme;
103: calculating the fitness of each individual in the initial population; the fitness of the individual represents the violation degree of the layout scheme corresponding to the individual on the position constraint information;
104: obtaining target individuals by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; obtaining a target layout scheme according to a target individual;
a1, A2, A3: a target area;
t: an individual;
401: acquiring initial layout planning information;
402: performing coding operation on the initial position information and the layout attribute information of the target area contained in the initial layout rule information to obtain individuals T of an initial population;
403: determining weight values for position constraint information among all target areas contained in the initial layout rule information, and setting fitness calculation formulas of all individuals;
404: defining super parameters of a genetic algorithm;
405: defining parameters of a genetic algorithm;
406: solving by adopting a genetic algorithm to obtain a target individual;
407: performing decoding operation on the target individual to obtain a candidate layout scheme;
408: calculating the adaptability of the candidate layout scheme;
409: the user manually selects from a plurality of layout schemes according to the calculated adaptability, so that a target layout scheme is obtained;
50: layout planning device
501: an information acquisition module;
502: a coding module;
503: a computing module;
504: the scheme obtains a module.
Detailed Description
In order to better understand the technical solutions in the embodiments of the present application, the following descriptions will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the embodiments of the present application shall fall within the scope of protection of the embodiments of the present application.
It should be noted that, the first and second in this application are merely for distinguishing names, and do not represent a sequential relationship, and should not be construed as indicating or implying relative importance or implying that the number of technical features indicated, e.g., the first user, the second user, the third user, is merely for distinguishing different users.
Embodiments of the present application are further described below with reference to the accompanying drawings of embodiments of the present application.
An embodiment of the present application provides a layout planning method, and fig. 1 is a flowchart illustration of the layout planning method provided in the embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step 101, acquiring initial position information, layout attribute information and position constraint information among target areas to be laid out; wherein the layout attribute information includes rotation information and/or candidate size information of the target area.
Specifically, in step 101, the obtained initial layout planning information may include: initial position information of target areas, layout attribute information, and position constraint information between the target areas.
The target area is any area to be deployed (laid out) inside a certain target space. For example: when the target space is a factory, the target area may be a process area or an equipment area. In the embodiment of the present application, the specific content and the number of the target areas are not limited.
Initial position information of the target area, which characterizes the position of the target area in the target space. In the embodiment of the present application, the specific representation form of the initial position information is not limited. For example: may be expressed in terms of two-dimensional (planar) coordinates, such as: in rectangular form, or in polar form, etc.
Optionally, in an embodiment of the present application, when the initial position information of the target areas characterizes the placement sequence between the target areas according to a preset placement principle.
Specifically, in general, after the placement rule of the target area is determined, the location information of each target area may be determined uniquely by the placement order, so in some embodiments of the present application, the placement order characterizing each target area may also be adopted as the initial location information of each target area under the preset placement rule. Compared with the mode of adopting plane coordinates as initial position information, the mode of adopting the placement sequence as the initial position information can effectively reduce the data processing amount in the coding operation process; and moreover, the searching efficiency of the genetic algorithm can be effectively improved.
The rotation information of the target area can be used for representing whether the target area can rotate in the layout planning process.
Candidate size information may characterize the desired size of the target area during layout planning. In layout planning, the area of the target area is generally known and fixed, and the size of the target area can have different values. For example: the area of a target area is known to be 24 square meters, and the shape of the target area is known to be rectangular, the candidate size corresponding to the target area may include: a length of 12m and a width of 2m; a length of 6m and a width of 4m; length is 8m, width is 3m; in addition, candidate sizes with non-integer lengths and widths are also possible, and are not listed here.
Optionally, in one embodiment of the present application, the position constraint information between the target areas characterizes a position constraint satisfied between the target areas, the position constraint including at least one of: adjacent constraints, mutually exclusive constraints, edge constraints, out-of-bounds constraints.
Specifically, the adjacency constraint means that the target areas must be adjacent to each other, that is: sharing a complete edge between target areas, or sharing partial areas in an edge; mutual exclusion constraint refers to that edges which are partially overlapped or completely overlapped do not exist between target areas along a specified direction; edge constraint refers to the edge position where the target area needs to be deployed in the target space, that is, a certain edge or edges of the target area need to be collinear with boundaries in the target space, for example: for target areas with ventilation or fire protection requirements, it is often necessary to set edge constraints; out-of-range constraints mean that the size of the target space may be beyond a certain range of standard sizes.
Referring to fig. 2, fig. 2 is a schematic diagram of position constraint in an embodiment of the present application. Wherein A1, A2 and A3 are target areas, wherein adjacent constraint is satisfied between A1 and A2; mutual exclusion constraints are satisfied between A1 and A3.
102, performing coding operation on initial position information and layout attribute information of each target area to obtain an initial population containing a plurality of individuals; wherein one individual corresponds to one layout scheme.
Specifically, when the layout attribute information acquired in step 101 includes rotation information and candidate size information, the position sequence, rotation sequence, and candidate size sequence may be correspondingly included in the individual, in which case step 102 may be implemented by the following procedure:
coding the initial position information, the rotation information and the candidate size information of the target area respectively to obtain a position sequence, a rotation sequence and a candidate size sequence of an individual in the initial population; the position sequence is used for representing initial position information, the rotation sequence is used for representing rotation information, and the candidate size sequence is used for representing candidate size;
fusing the position sequence, the rotation sequence and the candidate size sequence to obtain the individuals in the initial population.
Specifically, the rotation sequence may be represented in a binary manner, for example: non-rotatable with 0, rotatable with 1, etc. In the embodiment of the present application, the specific fusion manner among the position sequence, the rotation sequence and the candidate size sequence is not limited, and may be set in a user-defined manner according to actual situations. For example: for simplicity, the position sequence, the rotation sequence, and the candidate size sequence may be directly spliced to obtain individuals in the initial population.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an individual provided in an embodiment of the present application, where the first 3 boxes are a position sequence obtained after performing an encoding operation on initial position information of a target area; the middle 3 boxes are rotation sequences obtained after the rotation information of the target area is subjected to coding operation; the last 3 boxes are candidate size sequences obtained after the candidate size information of the target area is subjected to coding operation.
Step 103, calculating the fitness of each individual in the initial population; the fitness of the individual characterizes the violation degree of the layout scheme corresponding to the individual on the position constraint information.
Specifically, the greater the fitness of the individual, the higher the degree of violation of the position constraint information by the layout scheme corresponding to the individual is represented, or the greater the fitness of the individual, the lower the degree of violation of the position constraint information by the layout scheme corresponding to the individual is represented.
As above, the position constraints may generally comprise a plurality of different types, and thus, the degree of violation of the position constraint information by a layout scheme may be characterized by the number of position constraints violated by an individual corresponding layout scheme, wherein the greater the number, the higher the degree of violation is characterized and vice versa.
The degree of violation of the position constraint information by the layout scheme can be used to measure the reasonable degree (preference degree) of the layout scheme. Further, in other embodiments of the present application, other information may also be used to measure how reasonable the layout scheme is, for example: the total amount of material flow generated by material handling between different target areas, etc. Thus, alternatively, in one embodiment of the present application, the fitness of an individual may be calculated by:
calculating the total logistics amount of a layout scheme corresponding to each individual in the initial population, and obtaining a first fitness based on the total logistics amount; determining the total number of violations of the position constraint information violated by the layout scheme corresponding to the individual, and obtaining a second fitness based on the total number of violations;
and fusing the first fitness and the second fitness to obtain the fitness of the individual.
In this embodiment of the present application, the fusion manner between the first fitness and the second fitness is not limited, and may be set in a user-defined manner according to the actual situation. For example: for the convenience of calculation, the first fitness and the second fitness can be directly multiplied to obtain the fitness of an individual; for another example, in order to more accurately measure the reasonable degree of the layout scheme, weight values may be preset for the first fitness and the second fitness respectively, and then the first fitness and the second fitness are weighted and summed based on the preset weight values, so as to obtain the fitness of the individual.
The weight value of the second fitness may be set to one value in a unified manner, or may be set to a corresponding weight for each type of position constraint according to the type of position constraint. For the latter, the user can set different weights for different kinds of position constraints according to own preferences, and then, through the layout planning scheme provided by the embodiment of the application, the finally obtained target layout scheme can be more in line with personal preferences of the user. For example: compared with the adjacent constraint among the target areas, the user pays more attention to whether the target areas are at the edge positions of the target space, and at this time, the weight value corresponding to the adjacent constraint can be set to a smaller value, for example: 1, and the weight value corresponding to the edge constraint is set to a larger value, such as: and 5, the subsequent searching process adopting the genetic algorithm can be biased to the searching direction of the searching target area meeting the edge constraint, so that the target layout scheme obtained based on the searched target individual is more suitable for the user expectations.
104, obtaining target individuals by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; and obtaining a target layout scheme according to the target individual.
Specifically, after an initial population including a plurality of individuals is constructed and the fitness of each individual is calculated, the super parameters (cross operation related parameters, mutation operation related parameters, selection operation related parameters, etc.) and parameters (population size, population iteration number, the number of target individuals finally obtained, etc.) of the genetic algorithm can be set, and then, the genetic algorithm is adopted to perform optimization search, thereby obtaining the target individuals. After the target individual is obtained through the genetic algorithm, a final optimal target layout scheme can be obtained according to the obtained target individual.
In this embodiment of the present application, the number of the obtained target individuals may be set in a user-defined manner according to actual requirements, for example: the number of target individuals may be set to 1, or the number of target individuals may be set to a plurality. When the number of the target individuals is 1, a target layout scheme can be obtained through decoding operation of the target individuals; when the number of the target individuals is a plurality, the related information of the plurality of target individuals can be displayed in an interface for the user to select from.
Alternatively, in one embodiment of the present application, obtaining the target layout scheme according to the target individual may include:
updating the layout attribute information of the target areas and/or the position constraint information between the target areas according to the layout scheme corresponding to the target individuals and the adaptability of the target individuals;
based on the updated layout attribute information and/or the updated position constraint information, encoding to obtain an updated initial population containing a plurality of individuals;
calculating the fitness of each individual in the updated initial population, and obtaining a search result by adopting a genetic algorithm based on the fitness of each individual in the updated initial population and the updated population;
and selecting a target layout scheme meeting the requirements from the search results.
Further, if the target layout scheme meeting the requirement does not exist in the search result, returning to the step of updating the layout attribute information of the target area and/or the position constraint information between the target areas according to the layout scheme corresponding to the target individual and the adaptability of the target individual until a preset updating iteration stop condition is met;
and obtaining a target layout scheme based on the latest search result.
Specifically, when the target layout scheme meeting the user requirement does not exist in the result obtained by adopting the genetic algorithm, the input information (the layout attribute information of the target areas and/or the position constraint information between the target areas) of the genetic algorithm can be adjusted and updated based on the obtained target individual and the fitness of the individual, so that the target layout scheme is searched by adopting the genetic algorithm based on the updated information again, namely: and carrying out iterative search based on the updated information until a preset updating iteration stopping condition is met, for example: the latest search results have a layout scheme meeting the requirements, or the number of iterative updating reaches a preset number threshold, and the like.
Optionally, in an embodiment of the present application, obtaining the target layout solution according to the target individual may also include:
updating algorithm parameters of genetic algorithm information according to a layout scheme corresponding to a target individual and the adaptability of the target individual;
based on the initial population, obtaining a search result by adopting an updated genetic algorithm;
and selecting a target layout scheme meeting the requirements from the search results.
Further, if the target layout scheme meeting the requirement does not exist in the search result, returning to the step of updating the algorithm parameters of the genetic algorithm information according to the layout scheme corresponding to the target individual and the adaptability of the target individual until the preset updating iteration stop condition is met;
and obtaining a target layout scheme based on the latest search result.
Specifically, when the target layout scheme meeting the user requirement does not exist in the result obtained by adopting the genetic algorithm, parameters of the genetic algorithm (such as cross operation related parameters, mutation operation related parameters, super parameters of the genetic algorithm such as selection operation related parameters and the like) can be returned based on the obtained target individuals and the fitness of the individuals, and parameters of the genetic algorithm such as population size, population iteration times, the number of finally obtained target individuals and the like are adjusted and updated, so that the target layout scheme is searched again based on the genetic algorithm after parameter updating, namely: and carrying out iterative search based on the genetic algorithm after parameter updating until a preset updating iteration stopping condition is met, such as: the latest search results have a layout scheme meeting the requirements, or the number of iterative updating reaches a preset number threshold, and the like.
Referring to fig. 4, fig. 4 is a schematic step diagram of a layout planning process according to an embodiment of the present application. The following explains the layout planning scheme provided in the embodiment of the present application with reference to fig. 4:
step 401, obtaining initial layout planning information; step 402, performing coding operation on initial position information and layout attribute information of a target area contained in the initial layout rule information to obtain individuals T of an initial population; step 403, determining a weight value for the position constraint information between each target region contained in the initial layout rule information, and setting an fitness calculation formula of each individual; step 404, defining super parameters of a genetic algorithm; step 405, defining parameters of a genetic algorithm; step 406, solving by adopting a genetic algorithm to obtain a target individual; step 407, performing decoding operation on the target individual to obtain a candidate layout scheme; step 408, calculating the adaptability of the candidate layout scheme; step 409, the user manually selects from the plurality of layout schemes according to the calculated fitness, thereby obtaining the target layout scheme.
According to the layout planning method, the layout scheme is converted into individuals in the population by encoding the layout attribute information of each target area; the degree of violation of the layout scheme on the position constraint is calculated, so that the individual fitness is obtained; thereby converting the layout planning problem into an optimized search problem which can be solved by a genetic algorithm to obtain a target layout scheme. Therefore, the layout planning method and device can improve the rationality of the layout scheme while improving the layout planning efficiency.
In addition, in the embodiment of the application, when individuals in the initial population are constructed to search for the target layout scheme by adopting a genetic algorithm, not only the position change of each target area is considered, but also layout attribute information such as gesture rotation and/or size change which may exist in the layout process of each target area is considered; in addition, when generating the individual evaluation index (fitness), the position constraint condition existing between the target areas is also considered. Therefore, through the layout planning scheme provided by the embodiment of the application, a more reasonable layout scheme can be obtained.
Based on the layout planning method provided in any of the foregoing embodiments, the present embodiment provides a layout planning apparatus, as shown in fig. 5, fig. 5 is a schematic structural diagram of the layout planning apparatus provided in the present embodiment, and the layout planning apparatus 50 includes: an information acquisition module 501, an encoding module 502, a calculation module 503, and a scheme obtaining module 504.
An information obtaining module 501, configured to obtain initial position information of each target area to be laid out, layout attribute information, and position constraint information between each target area; the layout attribute information comprises rotation information and/or candidate size information of each target area;
the encoding module 502 is configured to perform an encoding operation on the initial position information and the layout attribute information of each target area, so as to obtain an initial population including a plurality of individuals; wherein one individual corresponds to one layout scheme;
a calculating module 503, configured to calculate fitness of each individual in the initial population; the fitness of the individual represents the violation degree of the layout scheme corresponding to the individual on the position constraint information;
a scheme obtaining module 504, configured to obtain a target individual by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; and obtaining a target layout scheme according to the target individual.
Optionally, in one embodiment of the present application, when the layout attribute information of the target area includes rotation information and candidate size information, the individual includes a position sequence, a rotation sequence, and a candidate size sequence;
the encoding module 502 is specifically configured to: coding the initial position information, the rotation information and the candidate size information of the target area respectively to obtain a position sequence, a rotation sequence and a candidate size sequence of an individual in the initial population; fusing the position sequence, the rotation sequence and the candidate size sequence to obtain the individuals in the initial population.
Optionally, in an embodiment of the present application, the calculating module 503 is specifically configured to: calculating the total logistics amount of a layout scheme corresponding to each individual in the initial population, and obtaining a first fitness based on the total logistics amount; determining the total number of violations of the position constraint information violated by the layout scheme corresponding to the individual, and obtaining a second fitness based on the total number of violations; and fusing the first fitness and the second fitness to obtain the fitness of the individual.
Optionally, in an embodiment of the present application, when the initial position information of the target areas characterizes the placement sequence between the target areas according to a preset placement principle.
Optionally, in one embodiment of the present application, the position constraint information between the target areas characterizes a position constraint satisfied between the target areas, the position constraint including at least one of: adjacent constraints, mutually exclusive constraints, edge constraints, out-of-bounds constraints.
Optionally, in an embodiment of the present application, the solution obtaining module 504 is specifically configured to, when performing the step of obtaining the target layout solution according to the target individual:
updating the layout attribute information of the target areas and/or the position constraint information between the target areas according to the layout scheme corresponding to the target individuals and the adaptability of the target individuals;
based on the updated layout attribute information and/or the updated position constraint information, encoding to obtain an updated initial population containing a plurality of individuals;
calculating the fitness of each individual in the updated initial population, and obtaining a search result by adopting a genetic algorithm based on the fitness of each individual in the updated initial population and the updated population;
and selecting a target layout scheme meeting the requirements from the search results.
Optionally, in an embodiment of the present application, the solution obtaining module 504, when executing the step of obtaining the target layout solution according to the target individual, is further configured to:
if the target layout scheme meeting the requirements does not exist in the search result, returning to the step of updating the layout attribute information of the target area and/or the position constraint information between the target areas according to the layout scheme corresponding to the target individual and the adaptability of the target individual until a preset updating iteration stop condition is met;
and obtaining a target layout scheme based on the latest search result.
Optionally, in an embodiment of the present application, the solution obtaining module 504 is specifically configured to, when performing the step of obtaining the target layout solution according to the target individual:
updating algorithm parameters of genetic algorithm information according to a layout scheme corresponding to a target individual and the adaptability of the target individual;
based on the initial population, obtaining a search result by adopting an updated genetic algorithm;
and selecting a target layout scheme meeting the requirements from the search results.
The layout planning device in the embodiment of the present application is configured to implement the corresponding layout planning method in the foregoing multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described herein again. In addition, the functional implementation of each module in the layout planning apparatus of the embodiment of the present application may refer to the description of the corresponding parts in the foregoing method embodiment, which is not repeated herein.
Based on the layout planning method described in any one of the foregoing embodiments, an embodiment of the present application provides an electronic device, including: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus; the memory is used for storing a computer program, and the processor is used for implementing the method described in any embodiment when executing the program stored on the memory.
Based on the layout planning method described in any of the above embodiments, the present application provides a computer storage medium storing a computer program which, when executed by a processor, implements the method described in any of the above embodiments.
It should be noted that, according to implementation requirements, each component/step described in the embodiments of the present application may be split into more components/steps, and two or more components/steps or part of operations of the components/steps may be combined into new components/steps, so as to achieve the purposes of the embodiments of the present application.
The above-described methods according to embodiments of the present application may be implemented in hardware, firmware, or as software or computer code storable in a recording medium such as a CD ROM, RAM, floppy disk, hard disk, or magneto-optical disk, or as computer code originally stored in a remote recording medium or a non-transitory machine-readable medium and to be stored in a local recording medium downloaded through a network, so that the methods described herein may be stored on such software processes on a recording medium using a general purpose computer, special purpose processor, or programmable or special purpose hardware such as an ASIC or FPGA. It is understood that a computer, processor, microprocessor controller, or programmable hardware includes a memory component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code that, when accessed and executed by the computer, processor, or hardware, implements the layout planning methods described herein. Furthermore, when a general-purpose computer accesses code for implementing the layout planning method shown herein, execution of the code converts the general-purpose computer into a special-purpose computer for executing the layout planning method shown herein.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
Those of ordinary skill in the art will appreciate that the elements and method steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the embodiments of the present application.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The above embodiments are only for illustrating the embodiments of the present application, but not for limiting the embodiments of the present application, and various changes and modifications can be made by one skilled in the relevant art without departing from the spirit and scope of the embodiments of the present application, so that all equivalent technical solutions also fall within the scope of the embodiments of the present application, and the scope of the embodiments of the present application should be defined by the claims.
Claims (11)
1. A layout planning method, wherein the method comprises:
acquiring initial position information, layout attribute information and position constraint information among target areas to be laid out; the layout attribute information comprises rotation information and/or candidate size information of each target area;
performing coding operation on the initial position information and the layout attribute information of each target area to obtain an initial population containing a plurality of individuals; wherein one individual corresponds to one layout scheme;
calculating the fitness of each individual in the initial population; the fitness of the individual represents the violation degree of the layout scheme corresponding to the individual on the position constraint information;
obtaining target individuals by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; and obtaining a target layout scheme according to the target individual.
2. The method according to claim 1, wherein when the layout attribute information of the target area includes rotation information and candidate size information, the individual includes a position sequence, a rotation sequence, and a candidate size sequence;
the encoding operation is performed on the initial position information and the layout attribute information of the target area to obtain an initial population including a plurality of individuals, including:
respectively carrying out coding operation on the initial position information, the rotation information and the candidate size information of the target area to obtain a position sequence, a rotation sequence and a candidate size sequence of an individual in an initial population;
and fusing the position sequence, the rotation sequence and the candidate size sequence to obtain individuals in the initial population.
3. The method of claim 1, wherein the calculating fitness of individuals in the initial population comprises:
calculating the total logistics amount of a layout scheme corresponding to each individual in the initial population, and obtaining a first fitness based on the total logistics amount; determining the total number of violations of the position constraint information violated by the layout scheme corresponding to the individual, and obtaining a second fitness based on the total number of violations;
and fusing the first fitness and the second fitness to obtain the fitness of the individual.
4. A method according to any one of claims 1-3, wherein the initial position information of the target areas characterizes a placement sequence among the target areas when the areas are placed according to a preset placement principle.
5. A method according to any of claims 1-3, wherein the position constraint information between the target areas characterizes position constraints satisfied between the target areas, the position constraints comprising at least one of: adjacent constraints, mutually exclusive constraints, edge constraints, out-of-bounds constraints.
6. A method according to any one of claims 1-3, wherein said deriving a target layout plan from said target individual comprises:
updating layout attribute information of a target area and/or position constraint information among the target areas according to a layout scheme corresponding to the target individual and the adaptability of the target individual;
based on the updated layout attribute information and/or the updated position constraint information, encoding to obtain an updated initial population containing a plurality of individuals;
calculating the fitness of each individual in the updated initial population, and obtaining a search result by adopting a genetic algorithm based on the fitness of each individual in the updated initial population and the updated population;
and selecting a target layout scheme meeting the requirements from the search results.
7. The method of claim 6, wherein the method further comprises:
if the target layout scheme meeting the requirements does not exist in the search result, returning to the step of updating the layout attribute information of the target area and/or the position constraint information between the target areas according to the layout scheme corresponding to the target individual and the fitness of the target individual until a preset updating iteration stop condition is met;
and obtaining a target layout scheme based on the latest search result.
8. A method according to any one of claims 1-3, wherein said deriving a target layout plan from said target individual comprises:
updating algorithm parameters of the genetic algorithm information according to the layout scheme corresponding to the target individual and the adaptability of the target individual;
based on the initial population, obtaining a search result by adopting an updated genetic algorithm;
and selecting a target layout scheme meeting the requirements from the search results.
9. A layout planning apparatus, wherein the apparatus comprises:
the information acquisition module is used for acquiring initial position information, layout attribute information and position constraint information among the target areas to be laid out; the layout attribute information comprises rotation information and/or candidate size information of each target area;
the coding module is used for carrying out coding operation on the initial position information and the layout attribute information of each target area to obtain an initial population containing a plurality of individuals; wherein one individual corresponds to one layout scheme;
the calculating module is used for calculating the fitness of each individual in the initial population; the fitness of the individual represents the violation degree of the layout scheme corresponding to the individual on the position constraint information;
the scheme obtaining module is used for obtaining target individuals by adopting a genetic algorithm based on the initial population and the fitness of each individual in the initial population; and obtaining a target layout scheme according to the target individual.
10. An electronic device, comprising: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for carrying out the method steps of any one of claims 1-8 when executing a program stored on a memory.
11. A computer storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any of claims 1-8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117828701A (en) * | 2024-03-05 | 2024-04-05 | 中国石油大学(华东) | Engineering drawing layout optimization method, system, equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117828701A (en) * | 2024-03-05 | 2024-04-05 | 中国石油大学(华东) | Engineering drawing layout optimization method, system, equipment and medium |
| CN117828701B (en) * | 2024-03-05 | 2024-05-24 | 中国石油大学(华东) | Engineering drawing layout optimization method, system, equipment and medium |
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