CN113112068A - Method and system for addressing and layout of public facilities in villages and small towns - Google Patents
Method and system for addressing and layout of public facilities in villages and small towns Download PDFInfo
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Abstract
The invention discloses a method and a system for the site selection layout of public facilities in villages and small towns, wherein the site selection layout optimization of the public facilities can establish a spatial data set of a corresponding area by reading data of alternative facility points, demand point distribution, a road traffic network and the like at an input end, input corresponding data in the data set into an established site selection model of the public facility layout optimization, calculate the public facility layout by a program, optimize the site selection of the public facility layout, and finally output the site selection result. The method can be applied to various fields of site selection decision, public facility layout adjustment and the like in village and town planning by planning departments, and has wide application prospect.
Description
Technical Field
The disclosure belongs to the field of digital urban and rural planning, and particularly relates to a method and a system for site selection and layout of public facilities of villages and towns.
Background
The invention is carried out under the era background of reducing the urban and rural gap, promoting the urban and rural equilibrium development and accelerating the basic public education service equalization construction. From 1978 to the present, the continuous and rapid economic growth of China in nearly 50 years brings huge benefits to people. However, in the process of rapid development of the economic society, the urban and rural binary structure contradiction caused by the gap between urban population and village population in the aspect of public service is increasingly prominent. The public education service equivalent to urban population can not be enjoyed by village and town population for a long time, and the regional difference and social group difference of the public service lead to the weakening of social fairness.
The problem of site selection optimization of public facilities has been an important problem in urban and rural regulations. The traditional public facility site selection method is usually based on experience and faces complicated and variable actual environmental conditions and excessive influence factors, and the subjective decision method is difficult to make rational and reasonable judgment from the scientific and rigorous point of view. In recent years, with the continuous development of information technology and computer analysis technology, the data acquisition way is richer and more convenient, so that under the guidance of meeting upper planning and actual requirements, a public facility site selection and optimization tool based on the existing data and capable of quickly and effectively providing a site selection scheme can be established.
At present, most of site selection tools are site selection simulation based on a classical model or a location allocation model (location allocation) of an ArcGIS platform, are often single optimization targets, cannot provide interfaces configured in relation to actual environmental conditions, and are difficult to consider multiple factors such as economy, efficiency and fairness in practice. And the algorithm efficiency and the optimization capability of the existing model under the multi-objective constraint are still a space for further improvement.
Therefore, the invention establishes a village and town public facility site selection layout decision system which gives consideration to multiple factors such as economy, efficiency and fairness.
Disclosure of Invention
Aiming at the defects of the prior art, the disclosure aims to provide a decision-making system for the site selection layout of public facilities of villages and small towns, and solves the problems of difficult site selection decision and public facility layout adjustment in public facility planning of villages and small towns in the prior art.
The purpose of the disclosure can be realized by the following technical scheme:
a method for implementing layout of public facilities in villages and towns is characterized by comprising the following steps:
1) data collection and input: acquiring and inputting a village and town data set comprising actual geographic information, population distribution, original facility layout, proposed facility points and a road traffic network;
inputting elevation data into a GIS (geographic information system) for elevation and gradient analysis, eliminating areas unsuitable for construction, screening alternative facility construction land suitable for public facility construction by combining related planning upper planning data, and simplifying the geometric center of each screened polygon as the geographic position of each polygon to form a proposed facility point; calling a Baidu map API through Python to crawl AOI data of residential areas in village and town ranges, simplifying the geometric center of each polygon in the AOI data as the geographic position of the polygon, and supplementing residential points by combining related planning data to form population distribution; assigning population data of each residential quarter according to the population information of the villages and the towns in the statistical yearbook; calling a Baidu map API through Python to crawl public facility POIs in a village and town range to form an original facility layout; the town area range is selected through an OSM (open Street map) middle box, road data are obtained, and the road is subjected to hierarchical processing according to different label types to form a road traffic network.
Further, the objective function is:
the final optimization scheme is as follows:
in the formula: the variable q is the actual utility construction number (wherein q is less than or equal to n); the constant m is the number of villager points; the constant n is the number of plots constructed by public facilities; constant wiPopulation weight for ith demand point(ii) a Constant DijThe distance of a road path from the villager point i to the corresponding facility point j is set; constant D'ijThe standardized distance value of the road path from the villager point i to the corresponding facility point j is obtained; variable xijE {0,1}, when x ij1 means that demand point i is served by facility point j, otherwise 0; variable yjE {0,1}, when y j1 means that facility point j is selected, otherwise 0;
2) an address selection model: and according to an objective function in the established public facility site selection model, modifying related parameters in the constraint conditions by combining the types of different public facilities, and establishing a village and town public facility layout optimization site selection model of a corresponding type.
2.1) optimization objectives in the site selection model include:
the number of selected facility points is the smallest and the weighted distances between all demand points and their corresponding facility points are the shortest. In the setting of the objective function, multiple objectives such as economy, efficiency, fairness and the like are considered, and the objective function is a balance among multiple objectives;
the economic efficiency is as follows: the construction quantity of the overall facility points is small, and the operation and construction cost is reduced;
efficiency: the sum of weighted distances from the served residents to the corresponding facility points is shortest;
fairness: the distance between each resident and the corresponding facility point is limited within a certain range, and the farthest distance is smaller;
2.2) setting relevant parameters in the constraint conditions corresponding to different types of public facilities:
the constraint conditions mainly include: construction capacity constraint of various public utility points, i.e. maximum capacity of facility CmaxMinimum capacity of facility CminBest service radius D of various public facility pointsmax；
2.3) simulated annealing Algorithm
The simulated annealing algorithm is mainly used for program optimization in the site selection model, in the program design, the program is initialized every time when running, the program randomly selects a group of solutions in the establishment points of the alternative facilities and calculates the corresponding objective functions, then a group of new solutions are generated under certain disturbance, the corresponding objective function values are calculated again, the generated new solutions and the objective function values of the previous solutions are compared, if the objective function values of the new solutions are superior to the objective function values of the previous solutions, the new solutions are received, and if not, whether the new solutions are received or not is determined according to the Metropolis criterion. And repeatedly iterating the processes until the temperature is reduced to a preset temperature, and outputting the current solution as the optimal solution of the program.
3) Data output and display: and finally, outputting an address selection result set, and outputting corresponding statistical information to the result.
Further, the distance adopts an actual road distance, after alternative facility building points and residential point demand points are determined, a Dijkstra algorithm is called to calculate the shortest actual road distance between each residential demand point and each alternative facility point, and a distance matrix is built.
Further, in the fairness calculation, the time from the residential point to the facility point, that is, facility accessibility, is calculated using the designed road speed per hour, and the accessibility condition, the service crowd ratio, and the like of each facility point are calculated and fed back in real time.
Further, a device for layout of public facilities in villages and towns comprises a method for selecting layout of public facilities in villages and towns.
Further, a storage device for storing a method of a rural public facility enforcement layout.
And further, outputting and visually displaying the final site selection result by the data output and display, and calculating the population proportion covered by each site selection scheme in the effective time.
Further, a village and town public facility layout system comprises a first acquisition module, a first receiving module, a first calculation module and a first output module;
the first acquisition module: the system is used for acquiring a village and town data set, which comprises actual geographic information, population distribution, original facility layout, proposed facility points and road traffic network information;
the first receiving module is used for receiving the information acquired by the first acquisition module, analyzing and converting various data according to the received information, and determining a vector point set and a vector demand point set which are finally constructed as alternative facilities and the demand quantity corresponding to each demand point;
a first calculation module: establishing different optimization targets according to different types of facilities, and according to an objective function:
the final optimization scheme is as follows:
completing the determination of the optimal construction scheme of the facility;
a first output module: and collecting the final address selection result, and outputting corresponding statistical information to the result.
The beneficial effect of this disclosure:
the invention provides a decision-making system for automatically optimizing a site selection layout of public facilities for villages and towns, wherein the site selection layout of the public facilities can evaluate the suitability of land construction by reading the geographic information, population distribution, current facilities and the like at an input end, select land parcels suitable for construction, calculate and optimize input data through different types of site selection models optimized by the layout of the public facilities, and finally output a site selection result. The method can be applied to various fields of site selection decision, public facility layout adjustment and the like in village and town planning by planning departments.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without mastering the relevant program base.
Fig. 1 is a flow chart of an embodiment of the present disclosure.
FIG. 2 is input alternate facility point data of an embodiment of the disclosure.
Fig. 3 is input terminal resident demand point data of the embodiment of the present disclosure.
Fig. 4 is a set of road traffic network vectors of an embodiment of the present disclosure.
Fig. 5 is a set of the resident demand vector points of the embodiment of the present disclosure.
FIG. 6 is a set of vector points for alternate facility construction of an embodiment of the present disclosure.
FIG. 7 is a distance matrix of demand points to facility points for an embodiment of the present disclosure.
FIG. 8 is a flow chart of a simulated annealing algorithm of an embodiment of the disclosure.
FIG. 9 is a result output display of an embodiment of the disclosure.
Fig. 10 is a result statistics and visualization of an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by one of ordinary skill in the art from the embodiments disclosed herein without making any creative effort, shall fall within the scope of protection of the present disclosure.
A decision-making system for automatically optimizing site selection layout of public facilities facing villages and towns comprises the following steps:
1) data input: according to program requirements, inputting alternative facility points, resident demand points and a road traffic network at an input end;
2) an address selection model: using an MATLAB programming language, according to an objective function in the established public facility site selection model, combining with relevant parameters in different public facility type modification constraint conditions, establishing a corresponding type village and town public facility layout optimization site selection model, automatically identifying input information through a computer, and analyzing and optimizing input data;
3) data output and display: and finally, outputting an address selection result set, and outputting corresponding statistical information to the result.
As an optimized address selection scheme, the implementation method for automatically optimizing the address selection layout of public facilities facing villages and towns comprises the following steps of 1):
the input data mainly comprises: alternative facility points, residential demand points and road traffic networks.
Alternative facility points: the file format of the candidate facility point vector point set is excel (. xls), and the file format comprises the serial number, longitude and latitude of the candidate facility point. Data needs to be located in sheet1 of excel, the first column of the excel data is the serial number of the alternative facility point, and the second column and the third column are longitude and latitude information respectively;
the demand points of residents are as follows: the file format of the resident demand point vector point set is excel (. xls), and the resident demand point vector point set comprises the serial number, the longitude and the latitude of the resident demand point, the population number corresponding to the demand point and the population weight corresponding to the population number. The calculation of population quantity needs to analyze the current population distribution, the population growth rate of a place and the population proportion of each age, predict the population growth condition of the next decade and the change condition of the demand quantity of corresponding public facilities, and determine the demand point and the demand quantity. The data need to be located in the sheet1 of excel, the first column of the excel data is the serial number of the demand point of the residents, the second column and the third column are respectively longitude and latitude information, and the third column is the population number corresponding to the demand point (the population number of the ith demand point of the residents is marked as P)iThe maximum value of the population quantity of all the resident demand points is PmaxThe minimum value of the population quantity of all the resident demand points is Pmin) The fourth column is the population weight w calculated from the population numberi；
Road traffic network: the file format of the road traffic network is cad, wherein roads at all levels are arranged hierarchically, and all roads are broken at intersections. The road traffic network mainly comprises roads at all levels, such as national roads, provincial roads, county roads, rural roads, village and town internal roads, and the like, and is classified by a computer, so that different driving speeds are given to the roads at all levels, and an undirected and authorized road traffic network is established;
as an optimized addressing scheme, the implementation method for automatically optimizing addressing layout of public facilities facing villages and towns comprises the following steps of 2):
the optimization part of the village and town public facility location decision system can be described as follows:
there are m villager points in villages and towns, and each villager point corresponds to a population PiN number of plots which are alternative for public facility construction are known, q points are selected from the n number of plots for public facility construction, and the construction number q of public facilities and the specific positions of the public facilities are determined in an attempt. Wherein m is the total number of villager points, and n is the total number of alternative facility construction points; the target function and constraint conditions of the village and town public facility site selection model are set as follows:
minimum weighted service distance:
minimum facility construction number:
min q (2)
simultaneously, the constraint conditions should be satisfied:
in the formula: the variable q is the actual utility construction number (wherein q is less than or equal to n); the constant m is the number of villager points; the constant n is the number of plots constructed by public facilities; constant wiThe population weight corresponding to the ith demand point; constant DijThe distance m is the road path distance from the villager point i to the corresponding facility point j; constant D'ijThe standardized distance value of the road path from the villager point i to the corresponding facility point j is obtained; variable xijE {0,1}, when xij1 means that demand point i is served by facility point j, otherwise 0; variable yjE {0,1}, when y j1 means that facility point j is selected, otherwise 0; constant DmaxMaximum service distance acceptable for the set residents; constant PiFor the ith demand pointThe number of people; constant CmaxMaximum value of utility construction capacity; constant CminMinimum value for utility construction capacity.
Formula (3) represents that the finally selected number of facility points is q; formula (4) indicates that each villager point can only be served by one facility; formula (5) shows that villagers at villager points can only go to selected facility points; formula (6) shows that the maximum service distance from a villager to a corresponding public facility point of the villager does not exceed a given threshold; the formula (7) indicates that the utility construction capacity needs to be within a predetermined range.
Since the service distance between a villager and its corresponding public facility point in the optimization target directly concerns the convenience of using facilities, the priority is higher compared with the number of facility construction. Due to the complex relationship between the two, accurate quantitative processing is difficult to carry out, so that the processing method in application mathematics is used for reference, the optimization target of the facility construction quantity is taken as a control factor of the objective function, the two optimization targets are mutually associated and restricted in the design of the whole objective function, and finally the whole target of minimizing the sum of the weighted distances from the demand points to the corresponding facility points is met under the condition that the quantity of the facility points is as small as possible; based on the above ideas, the optimization targets are integrated, the multi-objective function is sorted and converted into a single objective function, and a final objective function is established as the following formula 8:
the final optimization scheme is as follows:
as shown in FIG. 1: analyzing the input information through a computer, reading the established alternative public facility points and the established resident demand points, inputting a program according to a formula 8 to perform a simulated annealing algorithm, and taking a formula 9 as a final optimization target to obtain an optimal solution.
In the setting of the objective function, multiple objectives such as economy, efficiency and fairness are considered, the balance among multiple objectives is achieved, the economy mainly means that the number of newly added facility points is small, and the operation and construction cost is reduced; the efficiency mainly means that the sum of weighted distances from the served residents to the corresponding facility points is shortest; fairness refers to limiting the distance between a resident and its corresponding facility point to a certain range.
The distance is the actual road distance, after alternative facility building points and residential points are determined, a Dijkstra algorithm is called to calculate the shortest actual road distance between each residential point and each alternative facility point, and a distance matrix from the residential point to the facility point is built.
In the fairness calculation, the time from a resident point to a facility point, namely facility accessibility, is calculated by using the designed road speed per hour, the accessibility condition of each facility point, the service crowd ratio and the like are calculated, and feedback is given in real time.
As an optimized address selection scheme, the implementation method for automatically optimizing the address selection layout of public facilities facing villages and towns comprises the following steps of 4):
and outputting and visually displaying the final site selection result, and calculating the population proportion covered by each site selection scheme within effective time (the optimal service time of each facility specified in the specification), so that a decision maker can judge the site selection result more intuitively.
In order to make the technical method and the beneficial effects of the invention clearer, the invention is further described in detail with reference to the accompanying drawings and the 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. This embodiment will be described by taking the location of an education facility in Dandu mountain city, Danun county, Anhui province as an example.
1) Data input:
1.1) alternative points of installation: and calling a Baidu map API through Python to crawl public facility POIs labeled as 'education training' in the county scope of the Danish province, wherein each POI data comprises information such as names, longitudes, latitudes, addresses, categories and the like of geographic entities, and the original facility point layout is formed through further screening. And simplifying the construction land which is made in the upper planning and can be used for public facility construction, taking the geometric center of each construction land plot as the plot for simplification, and integrating numbers with the screened existing educational facility points to form alternative facility points. The file format of the candidate facility point vector point set is excel (. xls), and the file format comprises the serial number, longitude and latitude of the candidate facility point.
As shown in fig. 2 and 6: the data needs to be located in a sheet1 of excel, the first column of the excel data is the serial number of the alternative facility point, and the second column and the third column are longitude and latitude information respectively. The program reads the corresponding excel file and then converts the excel file into vector point population of alternative facility construction in the space;
1.2) residential demand points: and calling a Baidu map API through Python to crawl AOI data of residential areas in the county scope of the painting, simplifying the geometric center of each polygon in the AOI data as the geographic position of the polygon, and supplementing residential points by combining related planning data to form the distribution of the positions of the residential points. And assigning population data of each residential quarter according to the population information of the villages and the towns in the statistical yearbook to form population distribution. The file format of the resident demand point vector point set is excel (. xls), and the resident demand point vector point set comprises the serial number, the longitude and the latitude of the resident demand point, the population number corresponding to the demand point and the population weight corresponding to the population number.
As shown in fig. 3 and 5, the data needs to be located in a sheet1 of excel, the first column of the excel data is the serial number of the demand point of the resident, the second column and the third column are respectively longitude and latitude information, the third column is the population number corresponding to the demand point, and the fourth column is the population weight w calculated from the population numberi. The program reads a corresponding excel file and then converts the excel file into a resident demand vector point set in the space;
1.3) road traffic network as shown in fig. 4 and 7: the method comprises the steps of selecting a scope of the county in a frame in an OSM (open Street map) map, downloading and obtaining road data, and carrying out hierarchical processing on roads according to different label types to form a road traffic network. The file format of the road traffic network is cad, wherein roads at all levels are arranged hierarchically, and all roads are broken at intersections. A Dijkstra algorithm is called to calculate the shortest path from each demand point to each facility point, and the information is stored as a distance matrix from the demand point to the facility point, so that the program can be directly read conveniently each time;
2) an address selection model: inputting input end data into a program, setting parameters of model constraint conditions according to different types of public facilities by using an MATLAB programming language, and establishing a village and town public facility layout optimization address selection model according to a set optimization target;
as shown in fig. 8, the input information is automatically recognized by the computer, and the input data is analyzed and optimized by using the simulated annealing algorithm, and in this embodiment, the site selection of the public facility in the city of shandong county in Maanshan is taken as an example, and the program calculation optimization solution is performed. Set C according to school capacity limits specified in the Specificationmax＝4000，Cmin＝100，DmaxProgram optimization calculations were performed at 6000.
3) As shown in fig. 9-10, data output and display: and finally outputting the site selection result set, and finally selecting the education facility point 68 altogether, wherein the maximum service distance is 5.892km, the average service distance is 2.635km, the weighted total service distance is 769.672km, the maximum number of students corresponding to the selected education facility is 3330, and the minimum number of students is 118. And outputting corresponding statistical information to the result.
Principle of operation
The land use construction suitability can be evaluated by reading the geographic information, population distribution, current facilities and the like at the input end, land parcels suitable for construction are selected, the site selection model is optimized through the layout of different types of public facilities, the input result is calculated and optimized, and finally the site selection result is output. The method can be applied to various fields of site selection decision, public facility layout adjustment and the like in village and town planning by planning departments.
In the description herein, references to the description of "one embodiment," "an example," "a specific example," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the disclosure. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing illustrates and describes the general principles, principal features, and advantages of the present disclosure. It will be understood by those skilled in the art that the present disclosure is not limited to the embodiments described above, which are presented solely for purposes of illustrating the principles of the disclosure, and that various changes and modifications may be made to the disclosure without departing from the spirit and scope of the disclosure, which is intended to be covered by the claims.
Claims (10)
1. A method for implementing layout of public facilities in villages and towns is characterized by comprising the following steps:
1) data collection and input: acquiring and inputting a village and town data set, analyzing and converting various data according to input information, determining a vector point set which is finally used as an alternative facility construction, a demand quantity of a resident demand vector point set and each demand point, and a road traffic network, and forming a village and town space data set;
2) an address selection model: according to an objective function in a public facility site selection model established by collecting and inputting data in the step 1), modifying relevant parameters in constraint conditions by combining types of different public facilities, and establishing a village and town public facility layout optimization site selection model of a corresponding type;
according to an optimization target in the site selection model, the public facilities set relevant parameters in the constraint conditions, and an objective function is established as follows:
the final optimization scheme is as follows:
in the formula: variable q is actual utility construction quantity(wherein q is ≦ n); the constant m is the number of villager points; the constant n is the number of plots constructed by public facilities; constant wiThe population weight corresponding to the ith demand point; constant DijThe distance of a road path from the villager point i to the corresponding facility point j is set; constant D'ijThe standardized distance value of the road path from the villager point i to the corresponding facility point j is obtained; variable xijE {0,1}, when xij1 means that demand point i is served by facility point j, otherwise 0; variable yjE {0,1}, when yj1 means that facility point j is selected, otherwise 0;
3) data output and display: and finally outputting an addressing result set s, and outputting corresponding statistical information to the result.
2. The method of claim 1, wherein the data collection and input comprises: the method comprises the following steps of actual geographic information, population distribution, original facility layout, establishment of facility points and a road traffic network, and specifically comprises the following steps:
1.1) performing elevation and gradient analysis, removing areas which are not suitable for construction, and screening alternative facility construction land which is suitable for public facility construction by combining with related planning upper planning data;
1.2) simplifying the geometric center of each screened land parcel as the geographic position of the land parcel to form a proposed facility point; calling AOI data of residential areas in the range of villages and towns, simplifying the geometric centers of all blocks in the AOI data as the geographic positions of the blocks, and supplementing the residential points by combining related planning data to form population distribution;
1.3) assigning values to population data of each residential quarter according to population information of villages and towns in the statistical yearbook; calling public facilities POI in the range of the villages and towns to form an original facility layout;
1.4) acquiring road data, and carrying out classification processing on roads according to different label types to form a road traffic network;
1.5) data analysis and conversion: and analyzing and converting each item of data according to the input information, determining a vector point set which is finally used as an alternative facility construction, a demand quantity of the resident demand vector point set corresponding to each demand point, and a road traffic network, and forming a village and town space data set.
3. The method as claimed in claim 1, wherein the objective function is optimized by using a simulated annealing algorithm, each time a program is initialized during running, the program randomly selects a set of solutions from the alternative facility building points, calculates the corresponding objective function, generates a new set of solutions under certain disturbance, recalculates the corresponding objective function value, compares the objective function value of the new solution generated this time with that of the previous solution, receives the new solution if the objective function value of the new solution is better than that of the previous solution, otherwise determines whether to accept the new solution according to Metropolis criterion, and iterates the above processes repeatedly until the temperature is reduced to a preset temperature, and outputs the current solution as the final solution.
4. The method of claim 1, wherein the optimization objectives in the site model include:
the economic efficiency is as follows: the construction quantity of the overall facility points is small, and the operation and construction cost is reduced;
efficiency: the sum of weighted distances from the served residents to the corresponding facility points is shortest;
fairness: the distance between the residents to their corresponding facility points is limited to a certain range, and the farthest distance is small.
5. The method as claimed in claim 1, wherein the distance is an actual road distance, and after the alternative facility establishment point and the residential point demand point are determined, a Dijkstra algorithm is invoked to calculate a shortest actual road distance between each residential demand point and each alternative facility point, and establish a distance matrix.
6. The method as claimed in claim 1, wherein the fairness calculation calculates time from a residential site to a facility site, i.e. facility accessibility, by using a designed road speed per hour, calculates accessibility of each facility site, service crowd ratio, etc., and gives feedback to statistical data in real time.
7. A system for rural public facility placement, the system comprising a method for rural public facility placement according to claim 1.
8. A storage device for use in a method of storing a rural public utility enforcement layout as claimed in claim 1.
9. The method as claimed in claim 1, wherein the data output and display outputs and visually displays the final addressing result, and calculates the population proportion covered by each addressing scheme in the effective time.
10. A public facility layout system for villages and towns is characterized by comprising a first acquisition module, a first receiving module, a first calculation module and a first output module;
the first acquisition module: the system is used for acquiring a village and town data set, which comprises actual geographic information, population distribution, original facility layout, proposed facility points and road traffic network information;
the first receiving module is used for receiving the information acquired by the first acquisition module, analyzing and converting various data according to the received information, and determining a vector point set and a vector demand point set which are finally constructed as alternative facilities and the demand quantity corresponding to each demand point;
a first calculation module: establishing different optimization targets according to different types of facilities, and according to an objective function:
the final optimization scheme is as follows:
completing the determination of the optimal construction scheme of the facility;
a first output module: and collecting the final address selection result, and outputting corresponding statistical information to the result.
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