Emergency rescue resource scheduling optimization method based on dynamic programming

Abstract

The invention relates to the technical field of resource scheduling, in particular to an emergency rescue resource scheduling optimization method based on dynamic planning, which comprises the following steps of: acquiring a population density coefficient of each to-be-rescued point and a route point to each reachable to-be-rescued point of the to-be-rescued point; obtaining an initial resource demand degree of each to-be-rescued point; constructing a dynamic planning model to obtain weighted scheduling time planned to the target to-be-rescued point; obtaining the distance time from the target to-be-rescued point to each reachable to-be-rescued point and the resource arrival time of each reachable to-be-rescued point; obtaining a second resource demand degree of each reachable to-be-rescued point of the target to-be-rescued point; obtaining the weighted scheduling time of each reachable to-be-rescued point planned to the target to-be-rescued point; and the dynamic planning model plans again to obtain an emergency rescue resource scheduling route. The invention aims to analyze the influence of the resource demand degree of the to-be-rescued point along with the time change while dynamically planning the emergency rescue resource scheduling, so that the time factor is considered in the resource scheduling route.

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

[0006] 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: Obtain all the points awaiting rescue from the disaster map and collect the number of permanent residents at each point. 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. 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. 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.

[0007] Preferably, the specific steps for obtaining the initial resource demand include: 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; 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.

[0008] 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: 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. Preset rescue transport speed; 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. 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. 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.

[0009] Preferably, the specific steps for obtaining the second resource demand level include: 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. 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. 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. 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.

[0010] Preferably, the specific steps for obtaining the self-rescue coefficient include: Obtain the self-rescue coefficient of each reachable point to be rescued from the target point 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.

[0011] Preferably, the specific steps for obtaining the coordination and rescue coefficient include: Let the initial resource demand of the j-th reachable point from the i-th point in need of rescue be denoted as . ; 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: 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.

[0012] Preferably, the specific steps for obtaining the coordinated rescue point include: 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.

[0013] 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: The initial resource demand of each reachable point of the target rescue point is inversely weighted by the rescue urgency relief weight to obtain the second resource demand of each reachable point of the target rescue point.

[0014] 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: The assembly point of the rescue site is denoted as... ; Record the rescued individuals as follows: The rescued set is a one-dimensional sequence of points awaiting rescue. 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; The rescued collection was accessed. After arriving at the The weighted dispatch time for each waiting point is recorded as follows: ;initialization ; Let the stage scheduling time from the i-th point awaiting rescue to its j-th reachable point awaiting rescue be denoted as . ; The dynamic programming model's state transition equation from the i-th point to its j-th reachable point is as follows: in, The weighted scheduling time for reaching the j-th reachable rescue point from the i-th rescue point; To incorporate the j-th reachable point from the i-th point awaiting rescue into the already rescued set. middle; 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. 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; The function is for finding the minimum value; 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. ; The rescue team has now been fully assembled. The sequence of all points awaiting rescue is denoted as the emergency rescue resource dispatch route.

[0015] 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

[0016] 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.

[0017] 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

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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: 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.

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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: Obtain all the points awaiting rescue from the disaster map and collect the number of permanent residents at each point. 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. 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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: The preset proximity range, in this embodiment, is an area with a side length of 10km*10km centered on each point to be rescued; 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; 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.

[0031] 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.

[0032] 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.

[0033] 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: The assembly point of the rescue site is denoted as... ; Record the rescued individuals as follows: The rescued set is a one-dimensional sequence of points awaiting rescue. 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; The rescued collection was accessed. After arriving at the The weighted dispatch time for each waiting point is recorded as follows: ;initialization ; Let the stage scheduling time from the i-th point awaiting rescue to its j-th reachable point awaiting rescue be denoted as . ; The dynamic programming model's state transition equation from the i-th point to its j-th reachable point is as follows: 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; To incorporate the j-th reachable point from the i-th point awaiting rescue into the already rescued set. middle; 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. 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; Until When the dynamic programming ends.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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: 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. The preset rescue transport speed is 30 km / h in this embodiment. 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. 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. 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.

[0040] As an example, the travel time is obtained as follows: 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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. 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. 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. 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. 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. 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.

[0045] 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: Obtain the self-rescue coefficient of each reachable point to be rescued from the target point 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.

[0046] 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: Let the initial resource demand of the j-th reachable point from the i-th point in need of rescue be denoted as . ; Let the arrival time of resources from the j-th reachable point to the i-th point in need of rescue be denoted as . ; in, It is an exponential function with the natural constant as its base, used in one example of this embodiment for inverse proportional normalization.

[0047] 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.

[0048] 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: 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: 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.

[0049] 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.

[0050] 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.

[0051] 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: The initial resource demand of each reachable point of the target rescue point is inversely weighted by the rescue urgency relief weight to obtain the second resource demand of each reachable point of the target rescue point.

[0052] 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: 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.

[0053] 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.

[0054] 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: 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. 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.

[0055] 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.

[0056] 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: 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.

[0057] 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. .

[0058] The rescue team has now been fully assembled. The sequence of all points awaiting rescue is denoted as the emergency rescue resource dispatch route.

[0059] 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.

[0060] 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. An emergency rescue resource scheduling optimization method based on dynamic programming, characterized in that, The method includes the following steps: 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; 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. 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. 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.

2. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 1, characterized in that, The process of obtaining the population density coefficient of each point awaiting rescue and obtaining several waypoints from each point awaiting rescue to each accessible point in the elevation map includes: Obtain all the points awaiting rescue from the disaster map and collect the number of permanent residents at each point. 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. 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. 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.

3. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 1, characterized in that, The specific steps for obtaining the initial resource demand include: 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; 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.

4. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 1, characterized in that, The analysis elevates all points along the route from the target rescue point to each reachable rescue point, obtaining the travel time from the target rescue point to each reachable rescue point, and the resource arrival time at each reachable rescue point includes: 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. Preset rescue transport speed; 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. 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. 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.

5. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 1, characterized in that, The specific steps for obtaining the second resource demand level include: 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. 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. 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. 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.

6. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 5, characterized in that, The specific steps for obtaining the self-rescue coefficient include: Obtain the self-rescue coefficient of each reachable point to be rescued from the target point 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.

7. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 5, characterized in that, The specific steps for obtaining the coordination and rescue coefficient include: Let the initial resource demand of the j-th reachable point from the i-th point in need of rescue be denoted as . ; 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: 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.

8. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 5, characterized in that, The specific steps for obtaining the coordinated rescue point include: 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.

9. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 5, characterized in that, The step of correcting the initial resource requirement of each reachable point of the target point of rescue using the rescue urgency relief weight to obtain the second resource requirement of each reachable point of the target point of rescue includes: The initial resource demand of each reachable point of the target rescue point is inversely weighted by the rescue urgency relief weight to obtain the second resource demand of each reachable point of the target rescue point.

10. The emergency rescue resource scheduling optimization method based on dynamic programming according to claim 1, characterized in that, 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: The assembly point of the rescue site is denoted as... ; Record the rescued individuals as follows: The rescued set is a one-dimensional sequence of points awaiting rescue. 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; The rescued collection was accessed. After arriving at the The weighted dispatch time for each waiting point is recorded as follows: ;initialization ; Let the stage scheduling time from the i-th point awaiting rescue to its j-th reachable point awaiting rescue be denoted as . ; The dynamic programming model's state transition equation from the i-th point to its j-th reachable point is as follows: in, The weighted scheduling time for reaching the j-th reachable rescue point from the i-th rescue point; To incorporate the j-th reachable point from the i-th point awaiting rescue into the already rescued set. middle; 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. 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; The function is for finding the minimum value; 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. ; The rescue team has now been fully assembled. The sequence of all points awaiting rescue is denoted as the emergency rescue resource dispatch route.

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