Emergency rescue resource scheduling optimization method based on dynamic programming

By constructing a dynamic programming model based on population density and elevation distribution, the impact of self-rescue and coordinated rescue is analyzed, and the emergency rescue resource scheduling route is optimized. This solves the problem of rescue delay caused by changes in the state of the rescue point in the dynamic programming algorithm and achieves efficient resource scheduling.

CN120996527BActive Publication Date: 2025-12-16DALIAN V R GLOBAL VISION
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Patent Information

Application Number
CN202511525163.6
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-10-24
Publication Date
2025-12-16
Estimated Expiration
2045-10-24

AI Technical Summary

Technical Problem

Existing dynamic programming algorithms only consider the initial state of the rescue point in emergency rescue resource scheduling, and fail to effectively cope with the changing state of the rescue point as the arrival time of rescue resources increases, resulting in rescue delays.

Method used

By acquiring the population density coefficient and elevation distribution of the points awaiting rescue, a dynamic programming model is constructed to analyze the impact of self-rescue and coordinated rescue under the resource arrival time, optimize resource scheduling routes, and dynamically adjust resource demand and travel time to achieve the shortest possible arrival time at each point awaiting rescue.

Benefits of technology

Effectively optimize the allocation of emergency rescue resources, reduce rescue delays, improve resource utilization efficiency, conform to the actual conditions of each rescue point, and minimize time and transportation costs.

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Abstract

The present application relates to the technical field of resource scheduling, and particularly relates to an emergency rescue resource scheduling optimization method based on dynamic programming, which comprises the following steps: obtaining a population density coefficient of each to-be-rescued point and a road point to each reachable to-be-rescued point thereof; obtaining an initial resource demand degree of each to-be-rescued point; constructing a dynamic programming model to obtain a weighted scheduling time to a target to-be-rescued point; obtaining a road distance from the target to-be-rescued point to each reachable to-be-rescued point thereof and a resource arrival time of each reachable to-be-rescued point thereof; obtaining a second resource demand degree of each reachable to-be-rescued point of the target to-be-rescued point; obtaining a weighted scheduling time to each reachable to-be-rescued point of the target to-be-rescued point; and the dynamic programming model is planned again to obtain an emergency rescue resource scheduling route. The present application aims to dynamically program the emergency rescue resource scheduling, analyze the influence of the change of the resource demand degree of the to-be-rescued point with time, and make the resource scheduling route consider the time factor.
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Description

Technical Field

[0001] This invention relates to the field of resource scheduling technology, and specifically to an emergency rescue resource scheduling optimization method based on dynamic programming. Background Technology

[0002] While rapid social development brings numerous opportunities, it also poses a severe challenge to the level of emergency rescue technology. How to fully and rationally utilize existing resources and technologies, effectively dispatch emergency rescue forces within disaster-stricken areas, and ensure stable operation during emergencies has become an urgent issue. The rational allocation, layout, and dispatch of emergency resources are the foundation for the effective functioning of emergency command systems. Emergency rescue resource dispatch is a core issue in the field of operations optimization, aiming to maximize rescue effectiveness through scientific decision-making while minimizing time and transportation costs.

[0003] When dispatching emergency rescue resources, the arrival time of resources at each waiting point affects the subsequent rescue process. It depends on the current state and influences future developments. Therefore, dynamic programming algorithms are used to achieve rational dispatch of rescue resources. However, dynamic programming algorithms only consider the state of each waiting point at the time of planning. As the time for rescue resources to arrive at the waiting points increases, the current state of the waiting points also changes. Dispatching resources based solely on the state of the waiting points at the time of planning leads to rescue delays. Summary of the Invention

[0004] This invention provides an emergency rescue resource scheduling optimization method based on dynamic programming to solve existing problems.

[0005] The emergency rescue resource scheduling optimization method based on dynamic programming of the present invention adopts the following technical solution:

[0006] One embodiment of the present invention provides an emergency rescue resource scheduling optimization method based on dynamic programming, the method comprising the following steps:

[0007] Obtain the population density coefficient of each rescue point, and obtain several waypoints from each rescue point to each reachable rescue point on the elevation map;

[0008] The initial resource requirement of each rescue point is obtained based on the elevation distribution and population density coefficient in the vicinity of each rescue point; a dynamic programming model is constructed based on the initial resource requirement and the number of route points, and the weighted scheduling time to the target rescue point is obtained.

[0009] Analyze the elevation of all points along the route from the target rescue point to each of its reachable rescue points to obtain the travel time from the target rescue point to each of its reachable rescue points, and obtain the resource arrival time of each reachable rescue point of the target rescue point; use the initial resource demand degree to analyze the impact of coordinated rescue and self-rescue of each reachable rescue point of the target rescue point on the resource arrival time, and obtain the second resource demand degree of each reachable rescue point of the target rescue point; weight the second resource demand degree and the travel time to obtain the weighted scheduling time planned to each reachable rescue point of the target rescue point.

[0010] The dynamic programming model selects new target rescue points from all reachable rescue points based on the weighted scheduling time and re-plans until all rescue points are planned. The sequence of rescue points is then recorded as the emergency rescue resource scheduling route.

[0011] Preferably, obtaining the population density coefficient of each point to be rescued and obtaining several waypoints from each point to be rescued to each accessible point to be rescued in the elevation map includes:

[0012] Obtain all the points awaiting rescue from the disaster map and collect the number of permanent residents at each point.

[0013] The ratio of the number of permanent residents at each rescue point to the average number of permanent residents at all rescue points is recorded as the population density coefficient of each rescue point.

[0014] Obtain the elevation map of the disaster area and the shortest route between each point to be rescued in the elevation map. Other points to be rescued that are connected to each point to be rescued by the shortest route are recorded as reachable points to be rescued for each point to be rescued.

[0015] The shortest route from each point to be rescued to each of its reachable points to be rescued is divided according to a preset route interval, resulting in several route points from each point to be rescued to each of its reachable points to be rescued.

[0016] Preferably, the specific steps for obtaining the initial resource demand include:

[0017] Preset the proximity range; obtain the variance of the elevation within the proximity range of each rescue point in the elevation map, and record it as the elevation distribution of each rescue point;

[0018] The initial resource demand of each rescue point is obtained, and the initial resource demand is directly proportional to the elevation distribution and the population density coefficient.

[0019] Preferably, the step of analyzing the elevation of all road points from the target rescue point to each of its reachable rescue points, obtaining the travel time from the target rescue point to each of its reachable rescue points, and obtaining the resource arrival time for each reachable rescue point of the target rescue point includes:

[0020] In the elevation map, the variance of the elevation of the points on the route from the target point to each reachable point is recorded as the road condition influence coefficient from the target point to each reachable point.

[0021] Preset rescue transport speed;

[0022] The ratio of the number of route points from the target rescue point to each of its reachable rescue points to the rescue transportation speed is recorded as the transportation time required from each rescue point to each of its reachable rescue points.

[0023] By using the road condition impact coefficient to weight the transportation time, the travel time from the target rescue point to each of its reachable rescue points can be obtained.

[0024] The weighted scheduling time of the target rescue point and the sum of the travel time are recorded as the resource arrival time of each reachable rescue point from the target rescue point.

[0025] Preferably, the specific steps for obtaining the second resource demand level include:

[0026] Based on the initial resource demand of each reachable point of the target point of rescue, obtain the self-rescue coefficient of each reachable point of the target point of rescue under the resource arrival time.

[0027] Based on the difference in initial resource requirements between each reachable point of the target point of rescue and its coordinated rescue point, the coordinated rescue coefficient of each reachable point of the target point of rescue is obtained.

[0028] Based on the self-rescue coefficient and the coordinated rescue coefficient, the urgency relief weight of each reachable point to be rescued from the target point to be rescued is obtained; the urgency relief weight is positively proportional to both the self-rescue coefficient and the coordinated rescue coefficient.

[0029] The initial resource requirement of each reachable point of the target rescue point is corrected using the rescue urgency relief weight, resulting in the second resource requirement of each reachable point of the target rescue point.

[0030] Preferably, the specific steps for obtaining the self-rescue coefficient include:

[0031] Obtain the self-rescue coefficient of each reachable point of the target point to be rescued under the resource arrival time. The self-rescue coefficient is inversely proportional to the resource arrival time and directly proportional to the initial resource demand.

[0032] Preferably, the specific steps for obtaining the coordination and rescue coefficient include:

[0033] Let the initial resource demand of the j-th reachable point from the i-th point in need of rescue be denoted as . ;

[0034] Coordination rescue coefficient of the i-th point awaiting rescue and the j-th point reachable from the i-th point awaiting rescue. The calculation method is as follows:

[0035]

[0036] in, Let be the average initial resource requirement of the coordinated rescue point that is reachable from the i-th rescue point to the j-th rescue point. It is a linear normalization function.

[0037] Preferably, the specific steps for obtaining the coordinated rescue point include:

[0038] Each reachable point of the target point to be rescued is designated as a coordinated rescue point for each reachable point of the target point to be rescued.

[0039] Preferably, the step of adjusting the initial resource requirement of each reachable point of the target point of rescue using the rescue urgency mitigation weight to obtain the second resource requirement of each reachable point of the target point of rescue includes:

[0040] The initial resource demand of each reachable point of the target point of rescue is inversely weighted by the rescue urgency relief weight to obtain the second resource demand of each reachable point of the target point of rescue.

[0041] Preferably, the dynamic programming model selects new target rescue points from all reachable rescue points based on the weighted scheduling time, and re-plans the route until all rescue points have been planned. The sequence of rescue points is then recorded as the emergency rescue resource scheduling route, including:

[0042] The assembly point of the rescue site is denoted as... ;

[0043] Record the rescued individuals as follows: The rescued set is a one-dimensional sequence of points awaiting rescue.

[0044] Any point to be rescued is designated as the target point to be rescued, and the target point to be rescued is denoted as the i-th point to be rescued;

[0045] The rescued collection was accessed. After arriving at the The weighted dispatch time for each waiting point is recorded as follows: ;initialization ;

[0046] Let the stage scheduling time from the i-th point awaiting rescue to its j-th reachable point awaiting rescue be denoted as . ;

[0047] The dynamic programming model's state transition equation from the i-th point to its j-th reachable point is as follows:

[0048]

[0049] in, The weighted scheduling time for reaching the j-th reachable rescue point from the i-th rescue point;

[0050] To incorporate the j-th reachable point from the i-th point awaiting rescue into the already rescued set. middle;

[0051] To access the rescued collection The minimum weighted scheduling time to reach the j-th reachable point from the i-th reachable point is not necessarily after passing through all the points awaiting rescue.

[0052] To access the rescued collection The weighted scheduling time from all points awaiting rescue to the j-th reachable point awaiting rescue after passing through the i-th point awaiting rescue;

[0053] The function is for finding the minimum value;

[0054] The dynamic programming algorithm selects a new target rescue point from all reachable rescue points of the target rescue point, and then re-plans using all reachable rescue points of the new target rescue point until... At that time, the dynamic programming ends, and the complete rescue set is obtained. ;

[0055] The rescue team has now been fully assembled. The sequence of all points awaiting rescue is denoted as the emergency rescue resource dispatch route.

[0056] The beneficial effects of the technical solution of this invention are as follows: This invention obtains the population density coefficient of each point awaiting rescue and the elevation of several road points leading to each reachable point awaiting rescue; obtains the initial resource demand of each point awaiting rescue based on the elevation distribution and population density coefficient within its vicinity; quantifies the number of disaster victims and the disaster situation at each point awaiting rescue; constructs a dynamic programming model based on the initial resource demand and the number of road points, and obtains the weighted scheduling time planned to the target point awaiting rescue; constructs a dynamic programming model to obtain the shortest weighted time to reach each point awaiting rescue considering the disaster situation and the shortest time under the resource scheduling route; analyzes the elevation of all road points from the target point awaiting rescue to each reachable point awaiting rescue, obtains the travel time from the target point awaiting rescue to each reachable point awaiting rescue, and obtains the resource arrival time for each reachable point awaiting rescue; corrects the time consumed on the rescue path by analyzing the elevation; and uses the initial resource demand to analyze the target point awaiting rescue under the resource arrival time. Each reachable point awaiting rescue is affected by the coordinated rescue efforts of all its second reachable points awaiting rescue and the self-rescue efforts of those reachable points awaiting rescue, thus obtaining the second resource demand degree of each reachable point awaiting rescue for the target target. By analyzing the self-rescue efforts and the rescue situation of each point awaiting rescue when reaching each point awaiting rescue, the second resource demand degree at the time of reaching each reachable point awaiting rescue is obtained. The second resource demand degree and the travel time are weighted to obtain the weighted scheduling time for each reachable point awaiting rescue planned to the target target target. The dynamic programming model selects new target points awaiting rescue from all reachable points awaiting rescue according to the weighted scheduling time and replans until all points awaiting rescue are planned. The sequence of points awaiting rescue is recorded as the emergency rescue resource scheduling route. This invention analyzes the ideal rescue demand when rescue resources reach each point awaiting rescue, and adjusts the resource demand degree of each point awaiting rescue based on time, thereby making the dynamic programming model more consistent with the actual situation of each point awaiting rescue. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a flowchart illustrating the steps of the dynamic programming-based emergency rescue resource scheduling optimization method of the present invention. Detailed Implementation

[0059] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the dynamic programming-based emergency rescue resource scheduling optimization method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0061] The specific scheme of the emergency rescue resource scheduling optimization method based on dynamic programming provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0062] Please see Figure 1 The diagram illustrates a flowchart of an emergency rescue resource scheduling optimization method based on dynamic programming, according to an embodiment of the present invention. The method includes the following steps:

[0063] Step S001: Obtain the population density coefficient of each point to be rescued, and obtain several waypoints from each point to be rescued to each accessible point to be rescued in the elevation map.

[0064] When a geological disaster occurs, emergency rescue resources are transported from the starting point to various rescue points, and corresponding emergency rescue resources are allocated along the way to each rescue point. Emergency rescue resources include heavy machinery, rescue personnel, life support materials, medical resources, etc. Therefore, when dispatching emergency rescue resources, it is necessary to consider the disaster situation at the rescue points and plan the corresponding rescue routes.

[0065] The extent of the disaster is mainly related to the number of people and geological conditions at each rescue site. However, the more complex the geological conditions and the higher the population density at each rescue site, the more severe the disaster. Furthermore, the distance between rescue sites affects the transportation of rescue resources during emergency rescue operations, and road conditions are closely related to elevation after a geological disaster.

[0066] Therefore, this embodiment obtains the population density coefficient of each rescue point by acquiring the difference between the permanent population of each rescue point and the permanent population of other rescue points, in order to reflect the number of people affected by the disaster at each rescue point; and obtains the elevation map of the disaster area and the routes between each rescue point, and divides the routes into several waypoints to reflect the road conditions of the routes.

[0067] Specifically, the method for obtaining the population density coefficient of each rescue point and the route points from each reachable rescue point on the elevation map is as follows:

[0068] Obtain all the points awaiting rescue from the disaster map and collect the number of permanent residents at each point.

[0069] The ratio of the number of permanent residents at each rescue point to the average number of permanent residents at all rescue points is recorded as the population density coefficient of each rescue point.

[0070] The process involves obtaining an elevation map of the disaster area and the shortest routes between various points awaiting rescue. Other points awaiting rescue that are connected to each point awaiting rescue by a shortest route are recorded as reachable points for each point awaiting rescue. The shortest routes from each point awaiting rescue to each reachable point are divided according to a preset distance, resulting in several route points from each point awaiting rescue to each reachable point. In this embodiment, the distance is described using 1 km as an example.

[0071] It should be noted that if the shortest route cannot be completely divided according to the preset route interval, the number of route points is the number that can be divided according to the preset route interval.

[0072] Step S002: Obtain the initial resource demand of each rescue point based on the elevation distribution and population density coefficient in the vicinity of each rescue point; construct a dynamic programming model based on the initial resource demand and the number of route points, and obtain the weighted scheduling time planned to the target rescue point.

[0073] It should be noted that dynamic programming algorithms make decisions at each stage through planning and backtracking to achieve the best result throughout the process, thus influencing the current state and future development. When scheduling emergency rescue resources, it is necessary to minimize the time and transportation costs of the routes. Therefore, this embodiment analyzes the resource demand of each rescue point and quantifies the transportation costs to each rescue point based on the route points, thereby constructing a dynamic programming model.

[0074] When a geological disaster occurs, the larger the population at the rescue point, the more people may be injured under the same degree of geological disaster, and therefore the higher the demand for emergency rescue resources. The worse the local geological environment at the rescue point, the greater the impact of the same geological disaster. Therefore, this embodiment obtains the initial resource demand of each rescue point based on the elevation distribution and population density coefficient in the vicinity of each rescue point.

[0075] Preferably, the specific steps for obtaining the initial resource requirement of each rescue point based on the elevation distribution and population density coefficient in the vicinity of each rescue point include:

[0076] The preset proximity range, in this embodiment, is an area with a side length of 10km*10km centered on each point to be rescued;

[0077] Obtain the variance of the elevation within the vicinity of each rescue point in the elevation map, and record it as the elevation distribution of each rescue point;

[0078] The initial resource demand of each rescue point is obtained, and the initial resource demand is directly proportional to the elevation distribution and the population density coefficient.

[0079] As an example, this embodiment normalizes the product of the elevation distribution and population density coefficient of each rescue point using the minimax normalization algorithm, and records the result as the initial resource demand of each rescue point.

[0080] It should be noted that when dispatching emergency rescue resources, time and transportation costs must be taken into account, and priority should be given to reaching the rescue points with higher resource demand. The more road points between two rescue points, the farther the distance between the two rescue points is. Therefore, this embodiment quantifies transportation costs by using the initial resource demand and the number of road points, and constructs a dynamic programming model with the shortest weighted dispatch time after passing through all rescue points.

[0081] Preferably, the specific steps for constructing a dynamic programming model based on the initial resource demand and the number of waypoints, and obtaining the weighted scheduling time from the planned destination to the target rescue point, are as follows:

[0082] The assembly point of the rescue site is denoted as... ;

[0083] Record the rescued individuals as follows: The rescued set is a one-dimensional sequence of points awaiting rescue.

[0084] Any point to be rescued is designated as the target point to be rescued, and the target point to be rescued is denoted as the i-th point to be rescued;

[0085] The rescued collection was accessed. After arriving at the The weighted dispatch time for each waiting point is recorded as follows: ;initialization ;

[0086] Let the stage scheduling time from the i-th point awaiting rescue to its j-th reachable point awaiting rescue be denoted as . ;

[0087] The dynamic programming model's state transition equation from the i-th point to its j-th reachable point is as follows:

[0088]

[0089] in, The dynamic programming model accessed the set of rescued individuals. Then, the weighted scheduling time when arriving at the j-th reachable rescue point from the i-th rescue point;

[0090] To incorporate the j-th reachable point from the i-th point awaiting rescue into the already rescued set. middle;

[0091] To access the rescued collection The minimum weighted scheduling time to reach the j-th reachable point from the i-th reachable point is not necessarily after passing through all the points awaiting rescue.

[0092] To access the rescued collection The weighted scheduling time from all points awaiting rescue to the j-th reachable point awaiting rescue after passing through the i-th point awaiting rescue;

[0093] Until When the dynamic programming ends.

[0094] It should be noted that when the dynamic programming model performs the next dynamic programming iteration, the weighted scheduling time of the previous stage is known, that is, the weighted scheduling time of the i-th point to be rescued is known.

[0095] Step S003: Analyze the elevation of all road points from the target rescue point to each of its reachable rescue points to obtain the travel time from the target rescue point to each of its reachable rescue points, and obtain the resource arrival time of each reachable rescue point of the target rescue point; use the initial resource demand degree to analyze the impact of the coordinated rescue of all its second reachable rescue points and the self-rescue of the reachable rescue points on each reachable rescue point of the target rescue point under the resource arrival time, and obtain the second resource demand degree of each reachable rescue point of the target rescue point; weight the second resource demand degree and the travel time to obtain the weighted scheduling time planned to each reachable rescue point of the target rescue point.

[0096] It should be noted that when updating the state transition equation, the state transition equation is updated by comparing the weighted scheduling time from the target rescue point to its reachable rescue point and the time from other paths to the reachable rescue point. The weighted scheduling time from the target rescue point to its reachable rescue point is the weighted scheduling time through the target rescue point plus the stage scheduling time from the target rescue point to its reachable rescue point. Therefore, the smaller the stage scheduling time, the more likely the emergency rescue scheduling route obtained by dynamic programming will be to pass through the target rescue point to its reachable rescue point.

[0097] Based on the above, the weighted scheduling time for each point to be rescued in this embodiment is the sum of the stage scheduling times of every two points to be rescued in the rescued set. Since the rescued points with higher resource demand and lower transportation costs and time are the first to be rescued, the stage scheduling time in this embodiment is related to the travel time from the target point to be rescued to its reachable points and the resource demand of the reachable points to be rescued.

[0098] It should be further explained that the travel time represents the transportation cost and time from the target rescue point to each of its reachable rescue points. Due to the geological disaster, the worse the road conditions between the target rescue point and each of its reachable rescue points, i.e., the greater the elevation difference between the road points, the more road clearing is required during rescue, resulting in higher transportation costs. At the same time, the more road points there are, the longer the distance, and the more time is required for rescue at the ideal transportation speed. Therefore, this embodiment obtains the travel time from the target rescue point to each of its reachable rescue points by analyzing the elevation of all road points from the target rescue point to each of its reachable rescue points. Then, the weighted scheduling time of the target rescue point is combined with the travel time to obtain the resource arrival time of emergency rescue resources to each reachable rescue point of the target rescue point.

[0099] Preferably, the specific steps for analyzing the elevation of all road points from the target rescue point to each of its reachable rescue points, obtaining the travel time from the target rescue point to each of its reachable rescue points, and obtaining the resource arrival time at each reachable rescue point of the target rescue point are as follows:

[0100] In the elevation map, the variance of the elevation of the points on the route from the target point to each reachable point is recorded as the road condition influence coefficient from the target point to each reachable point.

[0101] The preset rescue transport speed is 30 km / h in this embodiment.

[0102] The ratio of the number of route points from the target rescue point to each of its reachable rescue points to the rescue transportation speed is recorded as the transportation time required from each rescue point to each of its reachable rescue points.

[0103] By using the road condition impact coefficient to weight the transportation time, the travel time from the target rescue point to each of its reachable rescue points can be obtained.

[0104] The weighted scheduling time of the target rescue point and the sum of the travel time are recorded as the resource arrival time of each reachable rescue point from the target rescue point.

[0105] As an example, the travel time is obtained as follows:

[0106] The normalized road condition impact coefficient is summed with 1 to obtain the road condition impact weight. The product of the road condition impact weight and the transportation time is recorded as the travel time.

[0107] It should be noted that in this embodiment, the road condition influence coefficient is normalized using the sigmoid function, and the normalization range is... The resource arrival time is the time, under ideal conditions, to reach each reachable point of the target rescue point, and the travel time is the time required to travel from the rescue point to each of its reachable points of rescue.

[0108] It should be noted that after a geological disaster, it takes time for emergency rescue resources to reach each rescue point. Before reaching each rescue point, the rescue points themselves will carry out rescue operations. In this embodiment, the initial resource demand of each rescue point reflects the disaster situation of each rescue point. The weaker the disaster situation of a rescue point and the longer it takes for emergency rescue resources to reach it, the higher the degree of self-rescue of the rescue point. At the same time, due to the different geological conditions and population in different regions, the disaster situation of different rescue points will be different. After a geological disaster, if the initial resource demand of a certain rescue point is high, while the initial resource demand of its reachable rescue points is low, the reachable rescue points will spontaneously launch rescue operations for the rescue point with the higher initial resource demand. Moreover, the longer it takes to reach the rescue point, the more coordinated rescue operations it will receive from the reachable rescue points.

[0109] Based on this, this embodiment analyzes the initial resource demand of all points to be rescued at the resource arrival time to reflect the self-rescue of the target point to be rescued and the impact of coordinated rescue from its reachable points to be rescued at the resource arrival time, thereby obtaining the second resource demand of each reachable point to be rescued of the target point to be rescued at the resource arrival time.

[0110] Preferably, the specific steps for obtaining the second resource demand degree of each reachable point of the target rescue point under the resource arrival time, using the initial resource demand degree analysis, are as follows: Each reachable point of the target rescue point is affected by the coordinated rescue efforts of all its second reachable points and the self-rescue efforts of the reachable points.

[0111] Based on the initial resource demand of each reachable point of the target point of rescue, obtain the self-rescue coefficient of each reachable point of the target point of rescue under the resource arrival time.

[0112] Each reachable point of the target point to be rescued is designated as a coordinated rescue point for each reachable point of the target point to be rescued.

[0113] Based on the difference in initial resource requirements between each reachable point of the target point of rescue and its coordinated rescue point, the coordinated rescue coefficient of each reachable point of the target point of rescue is obtained.

[0114] Based on the self-rescue coefficient and the coordinated rescue coefficient, the urgency relief weight of each reachable point to be rescued from the target point to be rescued is obtained; the urgency relief weight is positively proportional to both the self-rescue coefficient and the coordinated rescue coefficient.

[0115] The initial resource requirement of each reachable point of the target rescue point is corrected using the rescue urgency relief weight, resulting in the second resource requirement of each reachable point of the target rescue point.

[0116] Specifically, the method for obtaining the self-rescue coefficient of each reachable point from the target rescue point at the resource arrival time, based on the initial resource demand of each reachable point from the target rescue point, is as follows:

[0117] Obtain the self-rescue coefficient of each reachable point of the target point to be rescued under the resource arrival time. The self-rescue coefficient is inversely proportional to the resource arrival time and directly proportional to the initial resource demand.

[0118] As an example, the self-rescue coefficient of the j-th reachable point from the i-th point awaiting rescue, given the resource arrival time. The calculation method is as follows:

[0119] Let the initial resource demand of the j-th reachable point from the i-th point in need of rescue be denoted as . ;

[0120] Let the arrival time of resources from the j-th reachable point to the i-th point in need of rescue be denoted as . ;

[0121]

[0122] in, It is an exponential function with the natural constant as its base, used in one example of this embodiment for inverse proportional normalization.

[0123] It should be noted that when the initial resource requirement of the j-th reachable point of the i-th point to be rescued is 0, the self-rescue coefficient of the j-th reachable point of the i-th point to be rescued is set to 0 at the resource arrival time.

[0124] Furthermore, based on the difference in initial resource requirements between each reachable point of the target rescue point and its coordinated rescue point, the specific calculation method for the coordinated rescue coefficient of each reachable point of the target rescue point is as follows:

[0125] Coordination rescue coefficient of the i-th point awaiting rescue and the j-th point reachable from the i-th point awaiting rescue. The calculation method is as follows:

[0126]

[0127] in, Let be the average initial resource requirement of the coordinated rescue point that is reachable from the i-th rescue point to the j-th rescue point. For linear normalization functions, this embodiment uses the maximum and minimum value normalization function as an example for description.

[0128] It should be noted that when This indicates that the disaster situation of the j-th reachable point of the i-th rescue point is much greater than that of its coordinated rescue point, and the higher the probability and degree of rescue from its coordinated rescue point, the larger the value of the coordinated rescue coefficient. Conversely, when the disaster situation of the j-th reachable point of the i-th rescue point is less than that of its coordinated rescue point, it indicates that the probability and degree of rescue from its coordinated rescue point is smaller.

[0129] Furthermore, as an example, this embodiment denotes the product of the self-rescue coefficient and the coordinated rescue coefficient as the rescue urgency mitigation weight for each reachable point to be rescued from the target point to be rescued.

[0130] Furthermore, the specific method for obtaining the second resource requirement of each reachable point of the target point of rescue by correcting the initial resource requirement of each reachable point of rescue using the aforementioned rescue urgency mitigation weight is as follows:

[0131] The initial resource demand of each reachable point of the target point of rescue is inversely weighted by the rescue urgency relief weight to obtain the second resource demand of each reachable point of the target point of rescue.

[0132] As an example, the specific method for determining the second resource requirement for each reachable point from the target point to be rescued is as follows:

[0133] The product of the difference between 1 and the rescue urgency relief weight, and the initial resource demand of each reachable point of the target rescue point, is denoted as the second resource demand of each reachable point of the target rescue point.

[0134] Based on the above steps, the second resource demand degree of each reachable point of the target rescue point is obtained. In this embodiment, the stage scheduling time from the target rescue point to each reachable point of the target rescue point is obtained according to the second resource demand degree and the travel time. Then, combined with the weighted scheduling time of the target rescue point, the weighted scheduling time of each reachable point of the target rescue point is obtained.

[0135] Preferably, the specific steps for obtaining the weighted scheduling time for each reachable rescue point planned to the target rescue point by weighting the second resource demand and the travel time are as follows:

[0136] The product of the second resource demand degree of each reachable point of the target point to be rescued and the travel time from the target point to each reachable point to be rescued is recorded as the stage scheduling time from the target point to each reachable point to be rescued.

[0137] The sum of the weighted scheduling time of the target rescue point and the stage scheduling time from the target rescue point to each of its reachable rescue points is denoted as the weighted scheduling time of each reachable rescue point of the target rescue point.

[0138] Step S004: The dynamic programming model selects new target rescue points from all reachable rescue points of the target rescue point according to the weighted scheduling time, and re-plans until all rescue points are planned. Then, the sequence of rescue points is recorded as the emergency rescue resource scheduling route.

[0139] It should be noted that the dynamic programming model dynamically plans the shortest time by comparing the weighted scheduling time of each reachable point from the target point to each reachable point when traveling from each point to be rescued to each reachable point of the target point with the shortest weighted scheduling time when traveling from all points to be rescued in the rescued set S. Therefore, this embodiment uses the weighted scheduling time of each reachable point of the target point to reconstruct the updated state transition equation:

[0140]

[0141] in, The weighted scheduling time for reaching the j-th reachable rescue point from the i-th rescue point; To access the rescued collection After reaching all available rescue points, it is not necessary to pass through the i-th rescue point. The minimum weighted scheduling time to reach the j-th reachable rescue point from the i-th rescue point is given. To access the rescued collection The weighted scheduling time from all points awaiting rescue to the j-th reachable point awaiting rescue after passing through the i-th point awaiting rescue is the weighted scheduling time for each reachable point awaiting rescue from the target point awaiting rescue. To access the rescued collection After arriving at the Weighted dispatch time for each waiting rescue point Let be the stage scheduling time from the i-th point to its j-th reachable point, that is, the stage scheduling time from the target point to each of its reachable points. This is a function that takes the minimum value.

[0142] Furthermore, the dynamic programming algorithm selects a new target rescue point from all reachable rescue points of the target rescue point, and then re-plans using all reachable rescue points of the new target rescue point, until... At that time, the dynamic programming ends, and the complete rescue set is obtained. .

[0143] The rescue team has now been fully assembled. The sequence of all points awaiting rescue is denoted as the emergency rescue resource dispatch route.

[0144] It should be noted that the embodiments used in this example The model only represents negative correlations and constraints. The model output results are in... Within the interval, This is the input to this model; in specific implementations, it can be replaced with other models that have the same purpose. This embodiment is merely an example. The description will be based on a model, without making any specific limitations.

[0145] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic programming-based emergency rescue resource scheduling optimization method, characterized in that, The method comprises the following steps: obtaining a population density coefficient of each rescue point, and obtaining a plurality of route points of each rescue point to each reachable rescue point in an elevation map; obtaining an initial resource demand degree of each rescue point according to the elevation distribution and the population density coefficient of each rescue point in a neighboring range, constructing a dynamic programming model according to the initial resource demand degree and the number of the route points, and obtaining a weighted scheduling time of planning to a target rescue point; analyzing the elevation of all route points of the target rescue point to each reachable rescue point, obtaining a travel time from the target rescue point to each reachable rescue point, and obtaining a resource arrival time of each reachable rescue point of the target rescue point; analyzing the initial resource demand degree to obtain a second resource demand degree of each reachable rescue point of the target rescue point under the influence of the coordinated rescue of all second reachable rescue points and the self-rescue of the reachable rescue point; and obtaining a weighted scheduling time of planning to each reachable rescue point of the target rescue point by weighting the second resource demand degree and the travel time; the dynamic programming model selects a new target rescue point from all reachable rescue points of the target rescue point according to the weighted scheduling time to plan again until all rescue points are planned, and a sequence of the rescue points is recorded as an emergency rescue resource scheduling route.

2. The method of claim 1, wherein, The obtaining of the population density coefficient of each rescue point and the obtaining of the plurality of route points of each rescue point to each reachable rescue point in the elevation map comprise: obtaining all rescue points in a disaster map, and collecting a resident population number of each rescue point; recording a ratio of the resident population number of each rescue point to a mean value of the resident population numbers of all rescue points as a population density coefficient of each rescue point; obtaining an elevation map of the disaster map and a shortest route between each rescue point in the elevation map, and recording other rescue points connected with each rescue point by the shortest route as reachable rescue points of each rescue point; dividing the shortest route of each rescue point to each reachable rescue point by a preset route interval to obtain a plurality of route points of each rescue point to each reachable rescue point.

3. The method of claim 1, wherein, The specific obtaining steps of the initial resource demand degree comprise: presetting a neighboring range, and obtaining a variance of elevations in the neighboring range of each rescue point in the elevation map as an elevation distribution of each rescue point; obtaining an initial resource demand degree of each rescue point, the initial resource demand degree being in a positive proportional relationship with the elevation distribution and the population density coefficient.

4. The method of claim 1, wherein, The analysis of the elevations of all route points of the target rescue point to each reachable rescue point, the obtaining of the travel time from the target rescue point to each reachable rescue point, and the obtaining of the resource arrival time of each reachable rescue point of the target rescue point comprise: in the elevation map, recording a variance of the elevations of the route points of the target rescue point to each reachable rescue point as a road condition influence coefficient of the target rescue point to each reachable rescue point; presetting a rescue transportation speed; A ratio of a number of route points from a target rescue point to each reachable rescue point of the target rescue point to the rescue transportation speed is recorded as a transportation time required by each rescue point to each reachable rescue point of the target rescue point; The transportation time required by each rescue point to each reachable rescue point of the target rescue point is weighted by using the road condition influence coefficient to obtain a travel time from the target rescue point to each reachable rescue point of the target rescue point; An addition of the weighted scheduling time of the target rescue point and the travel time is recorded as a resource arrival time of each reachable rescue point of the target rescue point.

5. The method of claim 1, wherein, The specific obtaining step of the second resource requirement degree comprises: An autonomous rescue coefficient of each reachable rescue point of the target rescue point at the resource arrival time is obtained according to the initial resource requirement degree of each reachable rescue point of the target rescue point; A coordination rescue coefficient of each reachable rescue point of the target rescue point is obtained according to a difference between the initial resource requirement degree of each reachable rescue point of the target rescue point and a coordination rescue point of each reachable rescue point of the target rescue point; A rescue urgency relief weight of each reachable rescue point of the target rescue point is obtained according to the autonomous rescue coefficient and the coordination rescue coefficient; the rescue urgency relief weight is in a positive proportional relationship with the autonomous rescue coefficient and the coordination rescue coefficient; The initial resource requirement degree of each reachable rescue point of the target rescue point is corrected by using the rescue urgency relief weight to obtain a second resource requirement degree of each reachable rescue point of the target rescue point.

6. The method of claim 5, wherein, The specific obtaining step of the autonomous rescue coefficient comprises: The autonomous rescue coefficient of each reachable rescue point of the target rescue point at the resource arrival time is in an inverse proportional relationship with the resource arrival time and in a positive proportional relationship with the initial resource requirement degree.

7. The method of claim 5, wherein, The specific obtaining step of the coordination rescue coefficient comprises: Let the initial resource requirement degree of the jth reachable rescue point of the ith rescue point to be rescued be denoted as ; The coordination rescue coefficient of the jth reachable rescue point of the ith rescue point to be rescued The calculation method is as follows: wherein, is the mean of the initial resource requirement degree of the jth reachable rescue point of the ith rescue point to be rescued, is a linear normalization function.

8. The method of claim 5, wherein, The specific obtaining step of the coordination rescue point comprises: Each reachable rescue point of each reachable rescue point of the target rescue point is recorded as a coordination rescue point of each reachable rescue point of the target rescue point.

9. The method of claim 5, wherein, The step of correcting the initial resource requirement degree of each reachable rescue point of the target rescue point by using the rescue urgency relief weight to obtain the second resource requirement degree of each reachable rescue point of the target rescue point comprises: The initial resource requirement degree of each reachable rescue point of the target rescue point is inversely proportionally weighted by using the rescue urgency relief weight to obtain the second resource requirement degree of each reachable rescue point of the target rescue point.

10. The method of claim 1, wherein, The dynamic programming model selects a new target rescue point from all reachable rescue points of the target rescue point according to the weighted scheduling time to plan again until all rescue points are planned, and a sequence of the rescue points is recorded as an emergency rescue resource scheduling route, which comprises: Let the set of points to be rescued be denoted as ; Let the rescued set be denoted as ; the rescued set is a one-dimensional sequence set of points to be rescued; Any one rescue point is taken as a target rescue point, and the target rescue point is recorded as an ith rescue point; The rescued collection was accessed. After arriving at the The weighted dispatch time for each waiting point is recorded as follows: ;initialization ; Let the phase scheduling time from the ith to-be-rescued point to its jth reachable to-be-rescued point be denoted as ; An updated state transition equation of the dynamic programming model from the ith rescue point to a jth reachable rescue point of the ith rescue point is: wherein, is the weighted dispatch time for the jth reachable point of interest to reach the ith point of interest to be rescued; to incorporate the jth reachable to-be-rescued point of the ith to-be-rescued point into the rescued set in the middle; after accessing the rescued set the minimum weighted dispatch time of the jth reachable rescued point to the ith rescued point, without necessarily passing through the ith rescued point after accessing all the rescued points after having visited the rescued set the weighted dispatch time to the jth reachable rescued point of the ith rescued point after having visited all rescued points of the ith rescued point to minimize the function; The dynamic programming algorithm selects a new target rescue point from all reachable rescue points of the target rescue point, plans again using all reachable rescue points of the new target rescue point, and so on until the dynamic programming ends, and the complete rescue set is obtained ; The sequence of all the points to be rescued at this time is formed into a complete rescue set The sequence of all the points to be rescued at this time is formed into a complete rescue set

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