CN117114169A - Emergency material warehouse optimal location method and system based on comprehensive evaluation - Google Patents
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Abstract
The invention relates to a comprehensive evaluation-based emergency material warehouse optimal location method and system, and belongs to the field of geographic planning. The method comprises the steps of collecting multiple evaluation factor data of candidate points, and performing data cleaning and preprocessing; carrying out standardization processing on the evaluation factors of each candidate point and giving out the weight of each factor; calculating the comprehensive score of each candidate point, and determining the point with the highest score as the optimal site point; calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path; the visualization presents the relationship between the most preferred site point and other candidate points; selecting and adjusting the optimal site according to the requirements, and formulating an emergency material transportation scheme according to the conditions; and implementing and supervising the emergency material allocation scheme. The method and the system improve the operation efficiency of the emergency logistics warehouse to a certain extent, and improve the real-time responsiveness of the warehouse to the emergency logistics demand.
Description
Technical Field
The invention belongs to the field of geographic planning, and particularly relates to an emergency material warehouse optimal location method and system based on comprehensive evaluation.
Background
The emergency material warehouse is a material supply point which is specially set for solving the basic living demands of people in emergencies. It is mainly used for storing various emergency rescue materials, such as food, drinking water, tent, blanket, medical apparatus and instruments, fire-fighting equipment, etc. When an emergency occurs, the emergency material warehouse can rapidly distribute material, so that the life and property safety of people can be guaranteed.
At present, frequent emergency events have great influence on society and daily life, and also bring a lot of uncertainties to emergency rescue work. In order to effectively solve the problem, emergency material warehouse development is rapid, and meanwhile, higher requirements are also put forward for planning and site selection of key emergency material warehouse. The reasonable emergency material warehouse site selection can improve emergency logistics guarantee and logistics transportation efficiency, and emergency materials are guaranteed to be supplied to a demand point in the shortest time. Therefore, the optimal site of the emergency material warehouse has great significance in reasonably distributing limited emergency materials, developing high-effect emergency rescue work and the like. The system is not only a foundation stone for emergency disaster management work, but also a key link for smooth development of disaster response.
The traditional warehouse site selection method mostly adopts a gravity center method or an AHP analytic hierarchy process. The gravity center method is a method of determining an optimal site selection point by calculating the average positions of all candidate points, and is suitable for a case where there is no obvious limitation. The AHP analytic hierarchy process is a decision analysis method, and can decompose the problem into standards and factors with different hierarchies, provide weights for each factor and help a decision maker to make trade-offs and decisions among a plurality of factors. However, the single site selection method is subject to various limitations, does not perform actual space analysis, is asynchronous with real-time road network information, has poor actual application effect, and has unsatisfactory site selection results. Therefore, in the process of planning and selecting the emergency support material warehouse, a method and a system which have comprehensive consideration factors, combine road network information and analyze space and can objectively and scientifically perform the optimal site selection of the emergency material warehouse are urgently needed. The present invention has been made in view of such a real demand.
Disclosure of Invention
First, the technical problem to be solved
The invention aims to solve the technical problems of how to provide an optimal location method and an optimal location system for an emergency material warehouse based on comprehensive evaluation, so as to solve the problems that a single location method is subject to various limitations, does not perform actual space analysis, is asynchronous with real-time road network information, has poor actual application effect and is not ideal in location result.
(II) technical scheme
In order to solve the technical problems, the invention provides a comprehensive evaluation-based optimal location method for an emergency material warehouse, which comprises the following steps:
s1, collecting multiple pieces of evaluation factor data of candidate points, and performing data cleaning and preprocessing;
s2, carrying out standardization processing on the evaluation factors of each candidate point, and giving out the weight of each factor;
s3, calculating the comprehensive score of each candidate point, and determining the point with the highest score as the optimal site point;
s4, calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path;
s5, visually presenting the relationship between the most preferred site point and other candidate points, including distance, path, score, transportation time and cost information;
s6, selecting and adjusting the optimal site according to the requirements, and making an emergency material transportation scheme according to the situation;
and S7, implementing and supervising an emergency material allocation scheme, and updating and adjusting data and parameters according to the requirements.
The invention also provides a comprehensive evaluation-based emergency material warehouse optimal location system, which comprises: the system comprises a data collection module, a data storage module, a gravity center method module, an AHP analytic hierarchy process module, a GIS space analysis technology module, an urban road network information module, a comprehensive evaluation module and a visualization module;
the data collection module is used for collecting related geographic information data, urban road network data, population distribution data and other data related to site selection;
the data storage module is used for storing the collected data in a database so as to facilitate subsequent processing and inquiry;
the gravity center method module is used for calculating gravity center positions of different areas and evaluating the advantages and disadvantages of each candidate place according to the gravity center positions;
the AHP analytic hierarchy process module is used for carrying out weight distribution on each factor by using an AHP analytic hierarchy process so as to determine the score of each candidate place;
the GIS space analysis technology module is used for analyzing the reachability and traffic jam conditions of different places by utilizing the GIS space analysis technology so as to evaluate each candidate place;
the urban road network information module is used for calculating the distance between different places and the time required for reaching the different places by utilizing the urban road network information, and further evaluating the advantages and disadvantages of each candidate place;
the comprehensive evaluation module is used for comprehensively evaluating the results of the modules so as to determine an optimal site selection scheme;
the visual module displays the evaluation result in a visual form, so that a user can intuitively understand and make a decision.
(III) beneficial effects
The invention provides a comprehensive evaluation-based emergency material warehouse optimal location method and system, wherein in the process of planning and selecting an emergency material warehouse, a method combining a gravity center method, a GIS space analysis technology, an AHP (advanced high-performance liquid chromatography) analytic method and urban road network information is utilized, the method can comprehensively evaluate a plurality of evaluation factor data of candidate points, comprehensively evaluate the factors, select the point with the highest score as an optimal location point, and calculate the distance and the path between the optimal location point and other candidate points by using a geographic information technology, so that the emergency material transportation time and cost are determined, the operation efficiency of the emergency material warehouse is improved to a certain extent, and the real-time responsiveness of the warehouse to the emergency material flow demand is improved. Therefore, the invention plays an important role in the optimal planning and site selection of the emergency material warehouse.
Drawings
FIG. 1 is a flow chart of a method for optimally locating an emergency material warehouse based on comprehensive evaluation according to the invention;
FIG. 2 is a system composition diagram of the emergency materials warehouse most preferred location method based on comprehensive evaluation of the present invention.
Detailed Description
To make the objects, contents and advantages of the present invention more apparent, the following detailed description of the present invention will be given with reference to the accompanying drawings and examples.
The invention relates to an emergency material warehouse optimal location method and system based on comprehensive evaluation, in particular to an emergency material warehouse optimal location method and system by combining a gravity center method, an AHP (advanced high-performance liquid chromatography) analytic technique, a GIS (geographic information system) spatial analysis technique and urban road network information.
The invention relates to a comprehensive evaluation-based emergency material warehouse optimal location method and a system thereof. The method comprises the following steps: collecting a plurality of evaluation factor data of the candidate points, and performing data cleaning and preprocessing; carrying out standardization processing on the evaluation factors of each candidate point and giving out the weight of each factor; calculating the comprehensive score of each candidate point, and determining the point with the highest score as the optimal site point; calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path; the relationship between the most preferred site point and other candidate points is visually presented, and the relationship comprises information such as distance, path, score, transportation time, cost and the like; selecting and adjusting the optimal site according to the requirements, and formulating an emergency material transportation scheme according to the conditions; and implementing and supervising an emergency material allocation scheme, and updating and adjusting data and parameters according to the requirements. The system comprises data acquisition, evaluation, site selection, visualization and other modules, and can automatically execute the method and present the result in a visual mode.
The purpose of the invention is that: the method for combining the gravity center method, the GIS space analysis technology, the AHP analytic hierarchy process and the urban road network information is provided, and the planning and site selection requirements of the emergency material warehouse are met.
In order to achieve the above object, the present invention provides a method and a system for optimal location of an emergency material warehouse based on comprehensive evaluation, wherein the method comprises:
s1, collecting multiple pieces of evaluation factor data of candidate points, and performing data cleaning and preprocessing.
S2, carrying out standardization processing on the evaluation factors of each candidate point, and giving out the weight of each factor.
S3, calculating the comprehensive score of each candidate point, and determining the point with the highest score as the optimal site point.
And S4, calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path.
S5, visually presenting the relationship between the most preferred site point and other candidate points, including information such as distance, path, score, transportation time and cost.
S6, selecting and adjusting the optimal site according to the requirements, and making an emergency material transportation scheme according to the situation.
And S7, implementing and supervising an emergency material allocation scheme, and updating and adjusting data and parameters according to the requirements.
The invention also provides a system based on the optimal location method of the emergency material warehouse, which comprises: the system comprises a data collection module, a data storage module, a gravity center method module, an AHP analytic hierarchy process module, a GIS space analysis technology module, an urban road network information module, a comprehensive evaluation module and a visualization module;
(1) The data collection module collects relevant geographic information data, urban road network data, population distribution data and other data related to site selection.
(2) The data storage module is used for storing the collected data in a database so as to facilitate subsequent processing and inquiry.
(3) The gravity center method module calculates gravity center positions of different areas and evaluates the advantages and disadvantages of each candidate place according to the gravity center positions.
(4) The AHP analytic hierarchy process module performs weight distribution on each factor by using an AHP analytic hierarchy process to determine the score of each candidate place.
(5) The GIS space analysis technology module is used for analyzing the reachability, traffic jam condition and other factors of different places by utilizing the GIS space analysis technology, so as to evaluate each candidate place.
(6) The city road network information module calculates the distance between different places and the time required for reaching different places by utilizing the city road network information, and further evaluates the advantages and disadvantages of each candidate place.
(7) The comprehensive evaluation module is used for comprehensively evaluating the results of the modules so as to determine the optimal site selection scheme.
(8) The visual module displays the evaluation result in a visual form, so that a user can intuitively understand and make a decision.
Example 1:
FIG. 1 is a flow chart of a method for optimally locating an emergency material warehouse based on comprehensive evaluation according to the present invention. As shown in fig. 1, the method includes:
(1) And collecting a plurality of evaluation factor data of the candidate points, and performing data cleaning and preprocessing.
In particular implementations, an alternative candidate point range is determined: according to the requirements and conditions of emergency material allocation, an alternative candidate point range is determined, for example, a certain city, a certain area or a specific place and the like.
(11) Collecting relevant data: relevant data such as census, traffic flows, weather observations, environmental monitoring, land price statistics, etc. are collected as required by the evaluation factors. Data sources may include government agencies, public institutions, research institutions, corporate companies, and the like.
(12) Cleaning and validation data: and cleaning and verifying the collected data, removing abnormal data such as repetition, errors, deletion and the like, and checking and verifying the data to ensure the reliability and accuracy of the data.
(13) Data preprocessing: the data is pre-processed, e.g., normalized, weighted, clustered, dimension-reduced, etc., for subsequent comprehensive evaluation and selection operations.
Let the candidate point set be p= { P 1 ,p 2 ,…,p n }，
The evaluation factor set is f= { F 1 ,f 2 ,…,f m },
Where n represents the number of candidate points and m represents the number of evaluation factors.
In step (1), a plurality of evaluation factor data are collected, cleaned and preprocessed, and the accuracy and reliability of the system are improved, so that subsequent comprehensive evaluation and selection can be realized.
(2) And carrying out standardization processing on the evaluation factors of each candidate point, and giving weight to each factor.
In practice, the evaluation factors often relate to different dimensions and ranges, for example, census data and environmental pollution indexes may be of different orders of magnitude. To eliminate the variability between these factors and to ensure that they are comparable and additive, they are subjected to a normalization process. Normalization converts each factor to a score or standard score between 0 and 1 using min-max normalization, z-score normalization, etc.
For each evaluation factor f i Assume that its value range [ a i,min ,a i,max ]，
Normalized to values in the range of [0,1], namely:
min-max normalization:
z-score normalization:
wherein the method comprises the steps ofSum s i The mean and standard deviation of the ith evaluation factor are represented, respectively, and j represents the jth candidate point.
After normalization, the importance and weight of each factor are determined. This is done by expert consultation, questionnaire, data mining, etc. The factors and weights to be considered will also vary for different emergency material deployment scenarios and requirements.
For example, in emergency material allocation in a certain area, traffic convenience, population density and environmental pollution level may be the most important factors, while other factors such as land prices, meteorological conditions, etc. are secondary. According to the actual situation, a corresponding weight value of each factor is given, and a weighted average method and the like are used for calculating the comprehensive score of each candidate point.
And step (2) is a process of carrying out weight determination and weighted score calculation on the standardized evaluation factors, and directly influences the evaluation accuracy and the result reliability of the system. The weight of each factor is determined by a scientific and reasonable method, and is flexibly adjusted and updated according to actual requirements.
(3) The composite score for each candidate point is calculated and the point with the highest score is determined as the most preferred site point.
In the specific implementation, after the normalization and weighting treatment of the step (2), the scores and weights of a plurality of evaluation factors corresponding to each candidate point are obtained. Next, they are combined together to calculate a composite score for each candidate point.
The calculation method adopts simple weighted average or weighted geometric average and other methods, gives corresponding weighted proportion according to the weights of all factors, and then multiplies or adds all the scores to obtain the comprehensive score.
Determining the importance degree and weight of each evaluation factor can be accomplished by adopting expert consultation, questionnaire investigation, data mining and the like. Let the weight of the ith evaluation factor be w i Then there is
Next, each candidate point p is calculated j Is the combined score W of (2) j I.e.
Simple weighted average method:
wherein w is i The weight of the i-th evaluation factor is represented.
Weighted geometric averaging:
wherein w is i The weight of the i-th evaluation factor is represented.
For example, assuming that the evaluation factors include population density, traffic convenience, meteorological conditions, and land price, and the corresponding weights are 0.3, 0.4, 0.2, and 0.1, respectively, the factor scores corresponding to a certain candidate point are 0.5, 0.8, 0.6, and 0.7, respectively, and the overall score of the point is:
(0.3×0.5)+(0.4×0.8)+(0.2×0.6)+(0.1×0.7)＝0.62
after the comprehensive scores of all the candidate points are calculated, the point with the highest score is selected as the optimal site point, and the operations such as path calculation, visualization and the like are further carried out.
And step (3) combining the normalized and weighted evaluation factor scores, calculating the comprehensive score of each candidate point, and selecting the point with the highest score from the comprehensive score as the optimal site point. This step considers the importance and weight of each evaluation factor, as well as the interactions and effects between the different factors, to ensure the objectivity and effectiveness of the most preferred site.
(4) And calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path.
In practice, after the most preferred site point is determined, the distance and path between the point and other candidate points are further calculated, and emergency material transportation time and cost are predicted according to the distances and paths. For each candidate point p j ＝(x j ,y j ) Which is represented on a two-dimensional plane. Specifically, the integrated score W j And another evaluation factor (e.g. distance from the center of the city) are represented in a two-dimensional plane, i.e. (W) j ,d j ) Wherein d is j Representing the distance of the point to the centre of the city.
Then calculate the combined score center of gravity position g= (X) of all candidate points G ,Y G ) Wherein
Finally, the optimal candidate point can be determined according to the distance between each candidate point and the gravity center position, and the point closest to the gravity center position is the optimal site point.
The distance and path between candidate points are precisely calculated by existing map information and geographic information technologies such as GIS (geographic information system), GPS (global positioning system), etc. For example, when using GIS, path planning and navigation may be performed according to information such as map data, road network, traffic conditions, etc., so as to accurately calculate parameters such as length, time, and cost of each path.
After relevant parameters of each path are calculated, the actual requirements and conditions are combined, and the emergency material transportation scheme is formulated and adjusted. For example, an appropriate transportation method and vehicle are selected according to factors such as the type, number and emergency degree of goods, and an optimal transportation path and scheme are made in consideration of various factors such as safety, efficiency and cost.
And (4) calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path. The step fully considers the actual situation and the demand, combines various modern technologies and means, improves the transportation efficiency, reduces the cost and ensures the smooth implementation of emergency material allocation.
(5) The visualization presents relationships between the most preferred site points and other candidate points, including information on distance, path, score, time of transportation, and cost.
In particular, after the most preferred site point is determined, the relationship between the most preferred site point and other candidate points is visually presented so as to more intuitively know the information such as the distance, the path, the score, the transportation time, the cost and the like between the most preferred site point and the other candidate points. This process may be accomplished in the form of charts, maps, 3D models, and the like.
For example, when using charts, various statistical charts such as bar charts, scatter charts, line charts, etc. are designed to show the relationships and trends between different factors, respectively. When the map is used, information such as the position, the path, the distance and the like of each candidate point is drawn, and different types of points and line segments are distinguished by different colors or symbols, so that the difference and the connection of the points and the line segments are compared and analyzed. When using 3D models, a virtual substance space is created, simulating spatial relationships and variations between the various substances to aid understanding and decision making.
In addition, the system utilizes visualization techniques for interactive operations, i.e., real-time adjustment and updating of data and parameters through human-machine interfaces, for more flexible selection and analysis. For example, the weights and thresholds are adjusted by means of sliders, drop-down boxes, etc. in order to dynamically display different selection results and conclusions.
In summary, step (5) is to visually present the relationship between the most preferred site point and other candidate points, including information such as distance, path, score, time of transportation, and cost. The step fully considers the visual effect and user experience of the data, and adopts proper visual technology and means in combination with actual requirements and conditions so as to improve the understanding and decision-making efficiency of the data.
(6) And selecting and adjusting the optimal site according to the requirements, and making an emergency material transportation scheme according to the conditions.
In practice, after the preceding steps have been performed, a most preferred site and emergency material transportation scheme based on data analysis and calculation is obtained. In practical application, various changes and challenges, such as new disaster events, road closure, traffic paralysis and the like, need to be timely adjusted and optimized to better meet practical requirements and conditions.
Therefore, the main work of the step (6) is to modify and optimize the scheme of the emergency material allocation according to the actual situation and the requirement. Specifically, this process may include the following aspects:
(61) Information collection and analysis: relevant information such as the extent of damage to the disaster event, changes in the surrounding environment, supply and demand of supplies, etc. is collected and analyzed to understand the actual situation and demand.
(62) Scheme evaluation and comparison: and evaluating the effectiveness and feasibility of the current scheme, comparing the advantages and disadvantages of different schemes, and selecting the most suitable scheme for adjustment and optimization.
(63) Scheme modification and update: parameters, weights, thresholds, etc. involved in the scheme are modified and updated to accommodate new situations and requirements.
(64) Experiment and verification: experiments and verification are performed to check the feasibility and effectiveness of the solution, and the results are fed back and adjusted to further optimize the solution.
In a word, the step (6) is to modify and optimize the scheme of the emergency material allocation according to the actual situation and the requirement. The step is flexible in strain and combines different technologies and means to improve the efficiency and quality of the scheme and ensure the smooth implementation of emergency material allocation.
(7) And implementing and supervising an emergency material allocation scheme, and updating and adjusting data and parameters according to the requirements.
In specific implementation, the step (7) mainly includes the following aspects:
(71) Embodiments are described below: and (3) material allocation is carried out according to the confirmed scheme, including selecting proper transportation modes, vehicles, routes and the like, and grasping the progress of transportation.
(72) And (3) supervision and adjustment: the transportation process is monitored and regulated in real time, the discovery problem is solved in time, the arrival of materials at the destination is ensured, and the requirements are met.
(73) Summary and feedback: summarizing and feeding back the implementation condition of the scheme, analyzing the advantages and disadvantages of the scheme and the existing problems, and providing reference and reference for the next emergency material allocation.
In summary, step 7 is to implement and supervise the emergency material allocation scheme, and to summarize and feed back according to the results. The step closely focuses on actual conditions and demands, and the scheme is adjusted and optimized at any time in the transportation process so as to ensure the success of emergency material allocation, summarize experience and training and provide support for improving the emergency management capability and level.
The invention also provides a system based on the optimal location method of the emergency material warehouse, and the system composition is shown in figure 2.
A system for a method of optimally locating an emergency material warehouse based on comprehensive assessment comprising: the system comprises a data collection module, a data storage module, a gravity center method module, an AHP analytic hierarchy process module, a GIS space analysis technology module, an urban road network information module, a comprehensive evaluation module and a visualization module. Wherein:
(1) The data collection module collects relevant geographic information data, urban road network data, population distribution data and other data related to site selection. The module is used for the step (1).
(2) The data storage module is used for storing the collected data in a database so as to facilitate subsequent processing and inquiry. The module is used for the steps (1), (4), (5), (6) and (7).
(3) The gravity center method module calculates gravity center positions of different areas and evaluates the advantages and disadvantages of each candidate place according to the gravity center positions. The module is used for the step (4).
(4) The AHP analytic hierarchy process module performs weight distribution on each factor by using an AHP analytic hierarchy process to determine the score of each candidate place. The module is used for the step (3).
(5) The GIS space analysis technology module is used for analyzing the reachability, traffic jam condition and other factors of different places by utilizing the GIS space analysis technology, so as to evaluate each candidate place. The module is used for the step (4) and the step (5).
(6) The city road network information module calculates the distance between different places and the time required for reaching different places by utilizing the city road network information, and further evaluates the advantages and disadvantages of each candidate place. The module is used for the steps (4), (5) and (6).
(7) The comprehensive evaluation module is used for comprehensively evaluating the results of the modules so as to determine the optimal site selection scheme. The module is used for the step (6) and the step (7).
(8) The visual module displays the evaluation result in a visual form, so that a user can intuitively understand and make a decision. The module is used for the steps (4), (5), (6) and (7).
Example 2:
a method and system for selecting a most preferred site for an emergency materials warehouse, comprising:
(1) And collecting a plurality of evaluation factor data of the candidate points, and performing data cleaning and preprocessing.
(2) And carrying out standardization processing on the evaluation factors of each candidate point, and giving weight to each factor.
(3) The composite score for each candidate point is calculated and the point with the highest score is determined as the most preferred site point.
(4) And calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path.
(5) The visualization presents relationships between the most preferred site points and other candidate points, including information on distance, path, score, time of transportation, and cost.
(6) And selecting and adjusting the optimal site according to the requirements, and making an emergency material transportation scheme according to the conditions.
(7) And implementing and supervising an emergency material allocation scheme, and updating and adjusting data and parameters according to the requirements.
Further, the collecting the multiple evaluation factor data of the candidate points, and performing data cleaning and preprocessing includes: determining a candidate point range for selection; collecting relevant data according to the requirements of the evaluation factors; cleaning and verifying the collected data, and removing abnormal data such as repetition, errors, deletion and the like; and carrying out normalization, standardization, weighting, clustering and dimension reduction preprocessing on the data.
Further, the normalization processing is performed on the evaluation factors of each candidate point, and the normalization uses minimum-maximum normalization, z-score normalization and the like, so that each factor is converted into a score or standard score between 0 and 1.
Further, the calculation method adopts simple weighted average or weighted geometric average and other methods to give corresponding weighted proportion according to the weights of the factors, and then all the scores are multiplied or added to obtain the comprehensive score.
Further, the system comprises: the system comprises a data collection module, a data storage module, a gravity center method module, an AHP analytic hierarchy process module, a GIS space analysis technology module, an urban road network information module, a comprehensive evaluation module and a visualization module.
According to the method, in the process of planning and selecting the site of the emergency material warehouse, the gravity center method, the GIS space analysis technology, the AHP analytic hierarchy process and the urban road network information are utilized to be combined, the method can comprehensively evaluate a plurality of evaluation factor data of candidate points, the factors are comprehensively evaluated, the point with the highest score is selected as the optimal site point, the geographic information technology is utilized to calculate the distance and the path between the optimal site point and other candidate points, and therefore the emergency material transportation time and cost are determined, the operation efficiency of the emergency material warehouse is improved to a certain extent, and the real-time response of the warehouse to the emergency material flow demand is improved. Therefore, the invention plays an important role in the optimal planning and site selection of the emergency material warehouse.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (10)
1. The optimal location method for the emergency material warehouse based on comprehensive evaluation is characterized by comprising the following steps of:
s1, collecting multiple pieces of evaluation factor data of candidate points, and performing data cleaning and preprocessing;
s2, carrying out standardization processing on the evaluation factors of each candidate point, and giving out the weight of each factor;
s3, calculating the comprehensive score of each candidate point, and determining the point with the highest score as the optimal site point;
s4, calculating the distance and the path between the most preferred site point and other candidate points by using map information and geographic information technology, and predicting the emergency material transportation time and cost according to the distance and the path;
s5, visually presenting the relationship between the most preferred site point and other candidate points, including distance, path, score, transportation time and cost information;
s6, selecting and adjusting the optimal site according to the requirements, and making an emergency material transportation scheme according to the situation;
and S7, implementing and supervising an emergency material allocation scheme, and updating and adjusting data and parameters according to the requirements.
2. The method for optimal location of emergency supplies warehouse based on comprehensive evaluation according to claim 1, wherein said step S1 specifically comprises the steps of:
s11, collecting related data: collecting relevant data according to the requirements of evaluation factors, wherein the data sources comprise government departments, public institutions, research institutions and enterprise companies;
s12, cleaning and verifying data: cleaning and verifying the collected data, removing repeated, wrong and missing data, and checking and verifying;
s13, data preprocessing: preprocessing data, including: normalizing, weighting, clustering and dimension reduction to obtain a candidate point set and an evaluation factor set:
let the candidate point set be p= { P 1 ,p 2 ,…,p n }，
The evaluation factor set is f= { F 1 ,f 2 ,…,f m },
Where n represents the number of candidate points and m represents the number of evaluation factors.
3. The comprehensive assessment based emergency materials warehouse optimal location method as claimed in claim 2, wherein the data collected in S11 comprises: census, traffic flow, meteorological observations, environmental monitoring, and price statistics.
4. The method for optimal location of emergency supplies warehouse based on comprehensive evaluation according to claim 2, wherein said step S2 specifically comprises:
normalization converts each factor to a score or standard score between 0 and 1 using either min-max normalization or z-score normalization;
for each evaluation factor f i Assume that its value range [ a i,min ,a i,max ]，
Normalized to values in the range of [0,1], namely:
min-max normalization:
z-score normalization:
wherein the method comprises the steps ofSum s i Respectively representing the mean value and standard deviation of the ith evaluation factor, and j represents the jth candidate point;
after normalization, the importance and weight of each factor are determined, and this is done by expert consultation, questionnaire or data mining.
5. The method for optimal location of emergency supplies warehouse based on comprehensive evaluation according to claim 4, wherein said step S3 specifically comprises: a simple weighted average or weighted geometric average method is adopted, corresponding weighted proportion is given according to the weight of each factor, and then all the scores are multiplied or added to obtain a comprehensive score; each candidate point p j Is of the combined score of W j I.e.
Simple weighted average method:
wherein w is i A weight representing an ith evaluation factor;
weighted geometric averaging:
wherein w is i A weight representing an ith evaluation factor;
after the comprehensive scores of all the candidate points are calculated, the point with the highest score is selected as the most preferred site point.
6. The method for optimal location of emergency supplies warehouse based on comprehensive evaluation according to claim 5, wherein said step S4 specifically comprises:
after the most preferred site point is determined, further calculating the distance and the path between the point and other candidate points, and predicting the emergency material transportation time and cost according to the distance and the path;
for each candidate point p j ＝(x j ,y j ) Representing it on a two-dimensional plane; integrate it to score W j And another evaluation factor is represented in a two-dimensional plane, i.e. (W) j ,d j ) Wherein d is j Representing the distance of the point to the center of the city;
then calculate the combined score center of gravity position g= (X) of all candidate points G ,Y G ) Wherein
Finally, according to the distance between each candidate point and the gravity center position, the optimal candidate point can be determined, and the point closest to the gravity center position is the optimal site point;
through map information and geographic information technology, including: the GIS and the GPS accurately calculate the distance and the path between the candidate points; after relevant parameters of each path are calculated, the actual requirements and conditions are combined, and the emergency material transportation scheme is formulated and adjusted.
7. The method for optimally locating a comprehensive assessment-based emergency material warehouse according to claim 6, wherein in step S5, after the optimal location point is determined, the relationship between the optimal location point and other candidate points is visually presented so as to more intuitively understand the distance, path, score, transportation time and cost information between them; the process is completed by adopting a chart, a map and a 3D model mode; visualization techniques are utilized for interactive operations, i.e., real-time adjustment and updating of data and parameters through human-machine interfaces, for more flexible selection and analysis.
8. The method for optimal location of emergency supplies warehouse based on comprehensive evaluation according to claim 7, wherein said step S6 specifically comprises:
s61, information collection and analysis: collecting and analyzing relevant information, including: the hazard degree of disaster events, the change of surrounding environment and the supply and demand conditions of materials so as to know the actual conditions and demands;
s62, scheme evaluation and comparison: evaluating the effectiveness and feasibility of the current scheme, comparing the advantages and disadvantages of different schemes, and selecting the most suitable scheme for adjustment and optimization;
s63, scheme modification and updating: modifying and updating parameters, weights and thresholds involved in the scheme to adapt to new conditions and requirements;
s64, experiment and verification: experiments and verification are performed to check the feasibility and effectiveness of the solution, and the results are fed back and adjusted to further optimize the solution.
9. The emergency materials warehouse most preferred location method based on comprehensive evaluation as claimed in claim 8, wherein the step S7 of searching at speed specifically comprises:
s71, embodiment: material allocation is carried out according to the confirmed scheme, including selecting proper transportation modes, vehicles and routes, and grasping the progress condition of transportation;
s72, supervision and adjustment: the transportation process is monitored and regulated in real time, the discovery problem is solved in time, the arrival of materials at a destination is ensured, and the requirements are met;
s73, summary and feedback: summarizing and feeding back the implementation condition of the scheme, analyzing the advantages and disadvantages of the scheme and the existing problems, and providing reference and reference for the next emergency material allocation.
10. An emergency materials warehouse optimal location system based on comprehensive evaluation, characterized in that the system comprises: the system comprises a data collection module, a data storage module, a gravity center method module, an AHP analytic hierarchy process module, a GIS space analysis technology module, an urban road network information module, a comprehensive evaluation module and a visualization module;
the data collection module is used for collecting related geographic information data, urban road network data, population distribution data and other data related to site selection;
the data storage module is used for storing the collected data in a database so as to facilitate subsequent processing and inquiry;
the gravity center method module is used for calculating gravity center positions of different areas and evaluating the advantages and disadvantages of each candidate place according to the gravity center positions;
the AHP analytic hierarchy process module is used for carrying out weight distribution on each factor by using an AHP analytic hierarchy process so as to determine the score of each candidate place;
the GIS space analysis technology module is used for analyzing the reachability and traffic jam conditions of different places by utilizing the GIS space analysis technology so as to evaluate each candidate place;
the urban road network information module is used for calculating the distance between different places and the time required for reaching the different places by utilizing the urban road network information, and further evaluating the advantages and disadvantages of each candidate place;
the comprehensive evaluation module is used for comprehensively evaluating the results of the modules so as to determine an optimal site selection scheme;
the visual module displays the evaluation result in a visual form, so that a user can intuitively understand and make a decision.
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| CN117829557A (en) * | 2024-03-05 | 2024-04-05 | 安徽省大气探测技术保障中心 | Atmospheric chamber gas monitoring site selection method and system based on multi-technology integration |
| CN118134542A (en) * | 2024-05-06 | 2024-06-04 | 天津大学 | Position determining method and system for retail space |
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| CN117829557A (en) * | 2024-03-05 | 2024-04-05 | 安徽省大气探测技术保障中心 | Atmospheric chamber gas monitoring site selection method and system based on multi-technology integration |
| CN117829557B (en) * | 2024-03-05 | 2024-05-28 | 安徽省大气探测技术保障中心 | Atmospheric chamber gas monitoring site selection method and system based on multi-technology integration |
| CN118134542A (en) * | 2024-05-06 | 2024-06-04 | 天津大学 | Position determining method and system for retail space |
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