CN110852587A - Emergency shelter site selection and resource distribution method and system - Google Patents

Emergency shelter site selection and resource distribution method and system Download PDF

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CN110852587A
CN110852587A CN201911051200.9A CN201911051200A CN110852587A CN 110852587 A CN110852587 A CN 110852587A CN 201911051200 A CN201911051200 A CN 201911051200A CN 110852587 A CN110852587 A CN 110852587A
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王剑
沈丹青
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Huazhong University of Science and Technology
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Abstract

The invention discloses an emergency shelter site selection and resource distribution method and system, comprising the following steps: the method is characterized in that a grade difference thought is introduced on the basis of emergency shelter site selection and resource distribution process, victims and emergency shelters are graded according to injury degree and service level, and resource demand points of different grades have different priorities for resources; on the premise that the total capacity of the refuge station meets the total demand of the victims, a graded refuge site selection model is established with the aim of minimizing the total evacuation distance of the victims at low cost; on the basis of a location selection model for graded refuge, an allocation model is established with the aim of minimizing the amount of unsatisfied resources and considering the shortage of resources; combining the two models into one model, and simultaneously considering emergency shelter site selection and resource allocation; and solving the model by adopting a nesting algorithm. The invention provides a scheme capable of selecting addresses and distributing resources in consideration of different service levels of shelters and different resource priorities from the perspective of different injury degrees of victims.

Description

Emergency shelter site selection and resource distribution method and system
Technical Field
The invention relates to the technical field of emergency management planning, in particular to a method and a system for site selection and resource allocation of an emergency shelter.
Background
The emergency shelter is a disaster people arrangement measure for dealing with sudden public events, and in the post-disaster emergency management planning process, the emergency shelter is in a core position, can provide a temporary residence for disaster people, and helps the disaster people to avoid direct or indirect injuries caused by disasters. Therefore, whether the site selection of the emergency shelter is scientific and reasonable influences the level of the whole emergency management planning to a great extent. Meanwhile, the reasonable allocation of life and medical resources to the victims plays a crucial role in emergency management planning, and the basic life of the victims under the sudden accident can be guaranteed. Therefore, the method for reasonably selecting the emergency refuge and the efficient resource allocation method has very important strategic significance for emergency management planning.
In recent years, many scholars at home and abroad have studied emergency shelter site selection and emergency resource allocation, but most studies only consider one model, and relatively few studies are made on the overall system of emergency shelter site selection and corresponding resource allocation. Meanwhile, due to the complicated disaster situation after disaster, the disaster victims and their residences suffer different damage degrees, so the disaster victims with different injury degrees should be evacuated to refuges with different service levels to ensure the rescue quality of the disaster victims, however, the existing research on the site selection of emergency refuges with different service levels only considers the factors of the service time after disaster to grade the refuges: temporary shelters, short-term shelters and long-term shelters are few of site selection models for graded shelters considering different service levels at the same time after disaster. Furthermore, emergency resources tend to be in short supply at the beginning of an emergency, and few studies are available on emergency resource allocation in the case of insufficient resources.
Therefore, in order to meet the evacuation of victims at different levels and the corresponding emergency resource allocation, the invention of an emergency shelter site selection and resource allocation method which is in accordance with the reality, integrates a plurality of targets and constraints, considers the level difference and the insufficient resource condition, realizes quick evacuation response and efficient resource allocation is urgently needed.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to solve the technical problems that in the prior art, a scheme for ensuring the rescue quality of disaster victims by taking the disaster victims with different injury degrees into consideration to evacuate to refuges with different service levels and emergency resources are frequently in short supply and short demand at the initial stage of an emergency do not exist.
In order to achieve the above object, in a first aspect, the present invention provides a method for emergency shelter site selection and resource allocation, comprising the steps of:
s1, classifying victims and emergency shelters according to the injury degree of the victims and the service level of the emergency shelters; seriously injured victims should be evacuated to a high-grade emergency shelter;
s2, on the premise that the condition that the victims of different grades are evacuated to the emergency shelters of different grades is met, constructing an emergency shelter site selection model by taking the total evacuation distance of all the victims and the total construction cost of all the selected emergency shelters as targets to evacuate the victims of different grades to the corresponding emergency shelters; the evacuation distance refers to the distance from a disaster point where disaster people are located to an emergency shelter to be evacuated;
s3, on the basis of the emergency refuge site selection model, constructing a resource distribution model by taking the total transportation cost of the resources and the total resource quantity of the unmet disaster residents as targets under the condition of considering insufficient total resource supply; the resources comprise living resources and medical resources, and the transportation cost refers to the cost for transporting the resources from the resource distribution center to each disaster people placement point; the disaster people placement point comprises: disaster-affected sites and various emergency shelters;
s4, determining a total model considering emergency shelter site selection and resource allocation at the same time based on the emergency shelter site selection model and the resource allocation model;
s5, solving the general model by adopting a simulated annealing algorithm and a particle swarm optimization algorithm, and determining the site selection and resource allocation scheme of the emergency shelter.
Optionally, the step S1 specifically includes:
dividing the injury degree of the victims into the following parts according to a preset injury degree judgment standard: no injury, minor injury, and minor injury;
the emergency shelter is divided into a first-level emergency shelter and a second-level emergency shelter; the priority of the resources acquired by the primary emergency shelter is higher than that of the secondary emergency shelter; the service level provided by the primary emergency shelter is higher than that of the secondary emergency shelter;
wherein, the uninjured victims are arranged at the disaster-affected points of the victims, the slightly injured victims are arranged at the secondary emergency shelter, and the slightly injured victims are arranged at the primary emergency shelter.
Optionally, the emergency shelter addressing model includes two objective functions:
Figure BDA0002255372770000031
Figure BDA0002255372770000032
objective function f1Means minimizing the total evacuation distance of all victims; dajRepresenting the distance from the disaster-affected point a to the primary refuge j; dakRepresenting the distance from the disaster-affected point a to the secondary shelter k;the number of people evacuating from the disaster-affected point a to the first-level refuge j at the moment t is represented;
Figure BDA0002255372770000034
the number of people evacuating from the disaster-affected point a to a secondary refuge k at the moment t is represented;
objective function f2Represents minimizing the total construction cost of all selected emergency shelters; deltaj， Δ k0 or 1, whereinj0 indicates that the primary refuge j is not selected, Δ k0 indicates that the secondary shelter k is not selected, Δ j1 indicates that the primary refuge j is selected, Δ k1 indicates that the secondary shelter k is selected; cjRepresents the construction cost of the first-level shelter j, CkRepresents the construction cost of the secondary shelter k.
Optionally, the resource allocation model includes two objective functions:
Figure BDA0002255372770000042
objective function f3Represents minimizing the total transportation cost of the resource; ctrRepresents a unit transportation cost per unit resource; dcj，Dck，DcaRespectively showing the distance from the distribution center c to a primary refuge j, a secondary refuge k and a disaster affected point a;the quantity of the resources r conveyed from the distribution center c to the primary refuge j, the secondary refuge k and the disaster affected point a at the moment t is represented; omegaj，ωk，ωaRepresents the priority of resource demand points of three different levels, namely a first-level refuge j, a second-level refuge k and a disaster-affected point a, to the resource and omegaj+ωk+ωa＝1；
Objective function f4Represents the total number of resources that minimizes unmet disaster victims' needs;
Figure BDA0002255372770000044
Figure BDA0002255372770000045
respectively representing the quantity of the resources r which are not met by the primary refuge j, the secondary refuge k and the disaster-affected point a at the time t.
Optionally, the objective function of the overall model considering both emergency shelter addressing and resource allocation comprises: f. of1、f4And f5；f5＝f2+f3。
Optionally, the step S5 specifically includes the following steps:
s51, adopting a simulated annealing algorithm to f1、f4And f5The emergency shelters of all grades are selected as the objective function so as to respectively place all kinds of disaster victims,evacuating the corresponding disaster victims to a corresponding disaster site or an emergency shelter;
s52, adopting a particle swarm optimization algorithm to f3And f4And aiming at the target, resource allocation is carried out based on the site selection of the emergency shelter and the arrangement result of the disaster victims.
In a second aspect, the present invention provides an emergency shelter site selection and resource allocation system, comprising:
the grade dividing unit is used for dividing the victims and the emergency refuges into grades according to the injury degree of the victims and the service level of the emergency refuges; seriously injured victims should be evacuated to a high-grade emergency shelter;
the site selection model determination unit is used for constructing an emergency refuge site selection model by taking the total evacuation distance of all the victims and the total construction cost of all the selected emergency refuges as targets to evacuate the victims of different grades to the corresponding emergency refuges on the premise of meeting the requirement that the victims of different grades are evacuated to the emergency refuges of different grades; the evacuation distance refers to the distance from a disaster point where disaster people are located to an emergency shelter to be evacuated;
a resource allocation model determining unit, configured to construct a resource allocation model with the goal of minimizing the total transportation cost of resources and minimizing the total resource quantity of unmet disaster victims' needs, in consideration of the situation that the total resource supply is insufficient, on the basis of the emergency shelter site selection model; the resources comprise living resources and medical resources, and the transportation cost refers to the cost for transporting the resources from the resource distribution center to each disaster people placement point; the disaster people placement point comprises: disaster-affected sites and various emergency shelters;
a general model determination unit, configured to determine, based on the emergency shelter site selection model and the resource allocation model, a general model that simultaneously considers emergency shelter site selection and resource allocation;
and the model solving unit is used for solving the total model by adopting a simulated annealing algorithm and a particle swarm optimization algorithm to determine the site selection and resource allocation scheme of the emergency shelter.
Optionally, the ranking unit classifies the injury degree of the victims into: no injury, minor injury, and minor injury; the emergency shelter is divided into a first-level emergency shelter and a second-level emergency shelter; the priority of the resources acquired by the primary emergency shelter is higher than that of the secondary emergency shelter; the service level provided by the primary emergency shelter is higher than that of the secondary emergency shelter; wherein, the uninjured victims are arranged at the disaster-affected points of the victims, the slightly injured victims are arranged at the secondary emergency shelter, and the slightly injured victims are arranged at the primary emergency shelter.
Optionally, the emergency shelter addressing model includes two objective functions:
Figure BDA0002255372770000061
objective function f1Means minimizing the total evacuation distance of all victims; dajRepresenting the distance from the disaster-affected point a to the primary refuge j; dakRepresenting the distance from the disaster-affected point a to the secondary shelter k;
Figure BDA0002255372770000062
the number of people evacuating from the disaster-affected point a to the first-level refuge j at the moment t is represented;
Figure BDA0002255372770000063
the number of people evacuating from the disaster-affected point a to a secondary refuge k at the moment t is represented;
objective function f2Represents minimizing the total construction cost of all selected emergency shelters; deltaj， Δ k0 or 1, whereinj0 indicates that the primary refuge j is not selected, Δ k0 indicates that the secondary shelter k is not selected, Δ j1 indicates that the primary refuge j is selected, Δ k1 indicates that the secondary shelter k is selected; cjConstruction of the first-stage shelter jCost, CkRepresents the construction cost of the secondary shelter k.
Optionally, the resource allocation model includes two objective functions:
Figure BDA0002255372770000065
objective function f3Represents minimizing the total transportation cost of the resource; ctrRepresents a unit transportation cost per unit resource; dcj，Dck，DcaRespectively showing the distance from the distribution center c to a primary refuge j, a secondary refuge k and a disaster affected point a;
Figure BDA0002255372770000066
the quantity of the resources r conveyed from the distribution center c to the primary refuge j, the secondary refuge k and the disaster affected point a at the moment t is represented; omegaj，ωk，ωaRepresents the priority of resource demand points of three different levels, namely a first-level refuge j, a second-level refuge k and a disaster-affected point a, to the resource and omegaj+ωk+ωa＝1；
Objective function f4Represents the total number of resources that minimizes unmet disaster victims' needs;
Figure BDA0002255372770000071
Figure BDA0002255372770000072
respectively representing the quantity of the resources r which are not met by the primary refuge j, the secondary refuge k and the disaster-affected point a at the time t.
Generally, compared with the prior art, the above technical solution conceived by the present invention has the following beneficial effects:
the invention provides an emergency shelter site selection and resource allocation method and system, in the emergency shelter site selection and emergency resource allocation process, paying more attention to the overall benefits, not only considering the efficiency and the cost in the evacuation process of the disaster-stricken personnel, but also paying more attention to the combination of the subsequent resource allocation and the personnel evacuation to achieve the overall optimization, meanwhile, a refuge selected address model based on grade difference is provided based on the grade difference from the demand grade difference of disaster-stricken personnel, in the subsequent resource allocation process, the shortage of resources and the difference of different disaster-stricken personnel on the resource demand are considered, with three aspects of cost, efficiency and fairness as an integral target, a nesting algorithm based on the combination of a simulated annealing algorithm and a particle swarm optimization algorithm is provided for solving the multi-target model, the rapid response after the disaster can be realized, thereby providing efficient and practical decision reference for site selection and resource allocation of the post-disaster shelter.
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FIG. 1 is a schematic flow chart of the emergency shelter site selection and resource allocation method considering the grade difference according to the present invention;
FIG. 2 is a flow chart of the overall solving of the nesting algorithm in the emergency shelter site selection and resource allocation method considering the grade difference according to the present invention;
FIG. 3 is a flow chart of simulated annealing algorithm solving in the emergency shelter site selection and resource allocation method considering the grade difference;
FIG. 4 is a flow chart of a particle group optimization algorithm in the emergency shelter site selection and resource allocation method considering the grade difference according to the present invention;
FIG. 5 is an architecture diagram of an emergency shelter site selection and resource allocation system provided by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The invention provides an emergency shelter site selection and resource distribution method considering grade difference for overcoming the defects of shelter service level grade division and emergency resource distribution planning in emergency management in the prior art. The method is used for improving the practicability and the rationality of the emergency shelter site selection and the resource allocation method, and realizing quick evacuation response and efficient resource allocation.
In order to achieve the purpose, the invention adopts the technical scheme that: an emergency shelter site selection and resource allocation method considering grade difference, as shown in fig. 1, includes the following steps:
s1, introducing a grade difference thought on the basis of emergency shelter site selection and resource allocation process, and grading victims and emergency shelters according to the injury degree of the victims and the service level of the shelters;
s2, according to the grade determined in S1, on the premise that the capacities of different grades of refuges meet the demands of different grades of victims, a graded refuge site selection model is established with the goals of minimizing the total evacuation distance of the victims of each grade and low cost;
specifically, it is assumed that 20% of the victims are light-injured victims, 30% of the victims are light-injured victims, and the remaining 50% are non-injured victims; assuming that the total number of the victims suffered from the disaster in each period is known, the number of the victims with different injury degrees in each period can be known according to the assumption; assuming that the transport means are sufficient, i.e. under the condition of meeting the capacity requirement, the victims with different injury degrees at various periods can be always evacuated to the corresponding shelter.
S3, on the basis of the hierarchical refuge addressing model constructed in the S2, under the condition of resource insufficiency, establishing a resource distribution model with the aim of low cost and minimum unsatisfied resource amount;
specifically, assuming that the types and the amounts of resources required by the victims of the same injury type are the same, it can be known that the amount of resources required by each resource demand point at each period is also known according to the assumption that the number of the victims is known in S2;
it is assumed that the transport is sufficient, i.e. the allocated resources can always be allocated to the respective resource demand points.
S4, aiming at overall optimization, combining the two models S2 and S3 into one model, and considering emergency shelter site selection and resource allocation;
and S5, solving the model of S4 by adopting a nested algorithm (outer layer simulated annealing algorithm + inner layer particle swarm optimization algorithm), and determining the selection of the emergency shelter and a corresponding resource allocation scheme.
In S1, the specific method for ranking victims and emergency shelters according to the injury degree and service level is as follows:
the victims of disasters are divided into three grades according to different injury degrees: no injury, minor injury and minor injury (injury judged by medical professionals); the uninjured victims can be arranged at the disaster-affected point, the slightly injured victims are evacuated to the secondary refuge, and the slightly injured victims are evacuated to the primary refuge; the first-level shelter provides more comprehensive and good service than the second-level shelter, and has higher priority for acquiring emergency resources; the disaster victims with different grades have different priorities for resources, and the specific method comprises the following steps: the emergency resources are divided into two types, namely life resources and medical resources, so that the disaster people with high injury degree need more medical resources, the disaster people with low injury degree need more life resources, and the disaster people with high injury degree have higher priority on the resources.
In the step S2, the location model for the graded refuge is:
an objective function:
Figure BDA0002255372770000091
Figure BDA0002255372770000092
bundling conditions:
Figure BDA0002255372770000101
Figure BDA0002255372770000102
Figure BDA0002255372770000103
Figure BDA0002255372770000104
Figure BDA0002255372770000105
Figure BDA0002255372770000106
Figure BDA0002255372770000107
Figure BDA0002255372770000108
Figure BDA0002255372770000109
the objective function (1) represents that the total evacuation distance of victims in different levels is minimized; daj，DakRepresenting the distance from the disaster-affected point a to a primary refuge j and a secondary refuge k;
Figure BDA00022553727700001011
the number of people evacuating from the disaster-affected point a to a primary refuge j and a secondary refuge k at the moment t is shown; the objective function (2) represents the total construction cost of the minimum refuge; deltaj， Δ k0 or 1, Δj，Δ k0 denotes the primary refuge j, secondary refuge k is not selected, Δj，Δ k1 represents the primary refuge j, and a secondary refuge k is selected; cjRepresents the construction cost of the primary refuge j; ckRepresents the construction cost of the secondary shelter j.
Constraints (3) and (4) indicate that victims of different injury grades are all evacuated to corresponding grade of shelter,
Figure BDA00022553727700001012
the number of people needing to be evacuated to a first-level refuge j and a second-level refuge k in the disaster-affected point a at the moment t is shown; constraints (5) and (6) indicate that the people are evacuated from the disaster-affected point a to a primary refuge j, the total number of people in the secondary refuge k does not exceed the capacity of the primary refuge j and the secondary refuge k; MA (MA)j，MAkRepresenting the capacity of the primary refuge j and the secondary refuge k; the constraints (7) to (12) respectively represent the number of people in the primary refuge j, the secondary refuge k and the disaster-affected point a at different moments,
Figure BDA00022553727700001013
representing the number of people in the first-level refuge j at time t,
Figure BDA00022553727700001014
represents the number of people in the secondary refuge k at the moment t,
Figure BDA00022553727700001015
representing the number of people in the disaster-stricken point a at time t.
In S3, the resource allocation model is:
an objective function:
Figure BDA0002255372770000112
constraint conditions are as follows:
Figure BDA0002255372770000113
Figure BDA0002255372770000114
Figure BDA0002255372770000115
Figure BDA0002255372770000116
Figure BDA0002255372770000117
Figure BDA0002255372770000118
Figure BDA0002255372770000119
an objective function (13) represents minimizing the total transportation cost of the resource; ctrRepresents a unit transportation cost per unit resource; dcj，Dck，DcaThe distance from the distribution center c to a primary refuge j, a secondary refuge k and a disaster affected point a is shown;the quantity of the resources r conveyed from the distribution center c to the primary refuge j, the secondary refuge k and the disaster affected point a at the moment t is represented; omegaj，ωk，ωaRepresents the priority of resource demand points of three different levels, namely a first-level refuge j, a second-level refuge k and a disaster-affected point a, to the resource and omegaj+ωk+ω a1. An objective function (14) representing minimizing the total number of resources that do not meet the victim's demand;respectively representing the quantity of the resources r which are not met by the primary refuge j, the secondary refuge k and the disaster-affected point a at the moment t; the victims with different injury degrees have different priorities for resources, so that the victims with serious injury can obtain the resources preferentially, and the fairness of resource allocation is reflected.
Constraint (15) means that the total amount of resources r delivered from a distribution center c to a primary refuge j and a secondary refuge k does not exceed the total amount of resources in the distribution center c; delta C0 or 1, Δ C0 means that the distribution center c is not selected, Δ C1 indicates that the distribution center c is selected; MA (MA)rcIndicating the total amount of resources r in the distribution center c.
In the invention, the situation of insufficient resource distribution is considered, and in order to avoid resource waste, constraints (16), (17) and (18) indicate that the quantity of resources distributed to each resource demand point at each moment does not exceed the demand quantity;
Figure BDA0002255372770000124
and the demand quantities of the resource r of three different levels of resource demand points, namely a first-level refuge j, a second-level refuge k and a disaster-affected point a, are shown at the moment t.
Constraints (19), (20) and (21) represent the number of resources for which the respective resource demand points are not met at the respective times;
Figure BDA0002255372770000125
and the quantity of the resources r which are not met by the three resource demand points of different levels, namely the first-level refuge j, the second-level refuge k and the disaster-affected point a, is shown at the moment t.
In S4, the model considering emergency shelter addressing and resource allocation at the same time is:
an objective function:
Figure BDA0002255372770000126
f5＝min(∑jΔj*Cj+∑kΔk*Ck+∑t∑r∑c(∑jCtr*ωj*Dcj* (23)
Figure BDA0002255372770000132
the objective function (22) represents the minimization of the total evacuation distance of victims in different levels; an objective function (23) representing minimizing total costs, including construction costs of refuges and transportation costs of resources; an objective function (24) representing minimizing the total number of resources that do not meet the victim's demand; the constraints are as described in detail above.
In the step S5, the characteristic that the simulated annealing algorithm can temporarily accept some inferior solutions under the control of a certain probability is considered, and the characteristic can effectively avoid the solution from falling into local optimum, so the simulated annealing algorithm is used for realizing the refuge site selection of the outer layer; the particle swarm optimization algorithm realizes the search of the optimal solution in a complex space through the cooperation and competition among individuals and is suitable for solving the problem of complex scale, so the particle swarm optimization algorithm is adopted to solve the resource distribution of the inner layer, S4 is considered with the emergency shelter site selection and resource distribution model, a nested algorithm (outer layer simulated annealing algorithm + inner layer particle swarm optimization algorithm) is adopted to solve, the nested algorithm solving flow chart is shown in figure 2, the selection of the emergency shelter and the corresponding resource distribution scheme are determined, and the specific steps are as follows:
s51, the outer layer simulated annealing algorithm takes the whole target as an objective function, addresses of refuges of all levels are selected, so that various victims are respectively arranged, and the corresponding victims are evacuated to corresponding disaster-affected points or emergency refuges;
and S52, the inner-layer particle swarm optimization algorithm takes the optimized resource allocation model as a target, resource allocation is carried out based on the results of outer-layer addressing and personnel allocation, the allocation results are substituted into the outer-layer algorithm, and the whole objective function is calculated.
The solving flowchart of the outer layer simulated annealing algorithm in S51 is shown in fig. 3, and includes the following steps:
s511, converting the multi-target model of emergency shelter site selection and resource allocation in S4 into a single-target model, wherein the target function is a utility function of the simulated annealing algorithm, and the utility function is as follows:
Figure BDA0002255372770000133
wherein the content of the first and second substances,are three sub-goals of the model, ω1，ω2，ω3Weights for the three sub-targeting functions;
s512, initializing an algorithm: initialization Start temperature tsEnd temperature teThe method comprises the following steps of randomly generating an initial feasible solution s on the basis of meeting the total capacity of disaster evacuation requirements by using a temperature attenuation coefficient rho, an initial receiving probability epsilon and an iteration number K; the feasible solution s consists of 0 and 1, 0 representing that the alternative refuge is not selected, and 1 representing that the alternative refuge is selected.
S513, substituting the generated feasible solution S into a particle swarm optimization algorithm to obtain a resource allocation result, and calculating a utility function value f (S);
s514, generating a new solution S 'according to the iteration rule, calculating a utility function value f (S') of the new solution, and simulating the annealing algorithm to generate the new solution according to the following rule:
rule 1: randomly adding an unselected alternative refuge;
rule 2: on the premise of meeting the evacuation requirement of disaster victims, randomly reducing a selected refuge;
rule 3: and on the premise of meeting the evacuation requirements of the victims, randomly replacing one refuge (randomly adding one unselected alternative refuge and randomly reducing one selected refuge).
For example, assume that the initial solution s is:
1 0 0 1
the above description takes the addressing results of four shelters as an example, each bit of the initial solution s corresponds to the addressing result of one shelter, and the initial solution s represents the initial ΔjOr ΔkPossible solutions, 0 represents that the alternative refuge j or k is not selected, 1 represents that the alternative refuge j or k is selected,
then the new solution resulting from the initial solution s iteration may be, according to rule 1, rule 2 and rule 3:
(1)
Figure BDA0002255372770000141
(2)
Figure BDA0002255372770000142
(3)
s515, if the new solution f (S ') is better than the initial solution f (S), S ═ S ', f (S) ═ f (S '), otherwise, it is determined whether to accept the new solution according to Metropolis criterion:
Figure BDA0002255372770000151
where P represents the probability of accepting the new solution to the current solution, tkIs the current temperature.
S516, if the iteration number is reached, the next step is performed, otherwise k is k +1, and the process returns to S514;
s517, if the end temperature t is reachedk≤teIf not, returning the optimal solution s, otherwise, cooling tk＝ρ*tkReturning to S514.
As shown in fig. 4, the solving flowchart of the inner-layer particle swarm optimization algorithm in S52 includes the following steps:
s521, converting the resource allocation multi-target model in the S3 into a single-target model, wherein the target function is a fitness function of the particle swarm optimization algorithm, and the fitness function is as follows:
wherein the content of the first and second substances,
Figure BDA0002255372770000153
are two sub-targets of the model, ω'1，ω′2Weights for two sub-targeting functions;
s522, initializing the algorithm: initializing the population quantity N and the iteration times K, and generating an initial solution for resource allocation of each resource demand point, namely the initial position of the particle i according to the refuge site and the personnel allocation result obtained by the simulated annealing algorithm
Figure BDA0002255372770000154
Initial velocity of particle ii∈[1，N]；
S523, calculating fitness function of each particleObtaining a local optimum of the particle
Figure BDA0002255372770000157
And global optimum gbestk：
If it isThenIf it is
Figure BDA00022553727700001510
Then
Figure BDA00022553727700001511
S524, according to the current optimum of the particlesAnd global optimal gbest of all particleskUpdating the position and speed of each particle:
wherein w is an inertial weight, representing the ability of the particle to inherit the previous velocity;is the velocity of the kth iteration of particle i; c. C1And c2Is a learning factor; r is1And r2Is a random number between 0 and 1
S525, if the end condition is reached, namely K is equal to K, returning to the optimal solution gbestkOtherwise, return to S523.
Fig. 5 is an architecture diagram of an emergency shelter site selection and resource allocation system provided by the present invention, as shown in fig. 5, including:
a grade division unit 210 for dividing the victims and the emergency shelter into grades according to the injury degree of the victims and the service level of the emergency shelter; seriously injured victims should be evacuated to a high-grade emergency shelter;
the site selection model determining unit 220 is used for constructing an emergency refuge site selection model by aiming at minimizing the total evacuation distance of all the victims and minimizing the total construction cost of all the selected emergency refuges on the premise of meeting the condition that the victims at different grades are evacuated to the emergency refuges at different grades, so as to evacuate the victims at different grades to the corresponding emergency refuges; the evacuation distance refers to the distance from a disaster point where disaster people are located to an emergency shelter to be evacuated;
a resource allocation model determining unit 230, configured to construct a resource allocation model with the goal of minimizing the total transportation cost of resources and minimizing the total resource quantity of unmet disaster victims' needs, in consideration of the situation that the total resource supply is insufficient, on the basis of the emergency shelter site selection model; the resources comprise living resources and medical resources, and the transportation cost refers to the cost for transporting the resources from the resource distribution center to each disaster people placement point; the disaster people placement point comprises: disaster-affected sites and various emergency shelters;
a general model determination unit 240, configured to determine, based on the emergency shelter site selection model and the resource allocation model, a general model that simultaneously considers emergency shelter site selection and resource allocation;
and the model solving unit 250 is used for solving the total model by adopting a simulated annealing algorithm and a particle swarm optimization algorithm, and determining the site selection and resource allocation scheme of the emergency shelter.
Optionally, the ranking unit 210 classifies the injury degree of the victims into: no injury, minor injury, and minor injury; the emergency shelter is divided into a first-level emergency shelter and a second-level emergency shelter; the priority of the resources acquired by the primary emergency shelter is higher than that of the secondary emergency shelter; the service level provided by the primary emergency shelter is higher than that of the secondary emergency shelter; wherein, the uninjured victims are arranged at the disaster-affected points of the victims, the slightly injured victims are arranged at the secondary emergency shelter, and the slightly injured victims are arranged at the primary emergency shelter.
Optionally, the emergency shelter addressing model includes two objective functions:
Figure BDA0002255372770000171
Figure BDA0002255372770000172
objective function f1Means minimizing the total evacuation distance of all victims; dajRepresenting the distance from the disaster-affected point a to the primary refuge j; dakRepresenting the distance from the disaster-affected point a to the secondary shelter k;
Figure BDA0002255372770000173
the number of people evacuating from the disaster-affected point a to the first-level refuge j at the moment t is represented;the number of people evacuating from the disaster-affected point a to a secondary refuge k at the moment t is represented;
objective function f2Represents minimizing the total construction cost of all selected emergency shelters; deltaj， Δ k0 or 1, whereinj0 indicates that the primary refuge j is not selected, Δ k0 indicates that the secondary shelter k is not selected, Δ j1 indicates that the primary refuge j is selected, Δ k1 indicates that the secondary shelter k is selected; cjRepresents the construction cost of the first-level shelter j, CkRepresents the construction cost of the secondary shelter k.
Optionally, the resource allocation model includes two objective functions:
Figure BDA0002255372770000175
Figure BDA0002255372770000176
objective function f3Represents minimizing the total transportation cost of the resource; ctrRepresents a unit transportation cost per unit resource; dcj，Dck，DcaRespectively showing the distance from the distribution center c to a primary refuge j, a secondary refuge k and a disaster affected point a;
Figure BDA0002255372770000181
the quantity of the resources r conveyed from the distribution center c to the primary refuge j, the secondary refuge k and the disaster affected point a at the moment t is represented; omegaj，ωk，ωaRepresents the priority of resource demand points of three different levels, namely a first-level refuge j, a second-level refuge k and a disaster-affected point a, to the resource and omegaj+ωk+ωa＝1；
Objective function f4Represents the total number of resources that minimizes unmet disaster victims' needs;
Figure BDA0002255372770000183
respectively representing the quantity of the resources r which are not met by the primary refuge j, the secondary refuge k and the disaster-affected point a at the time t.
The functions of each unit can be referred to the detailed description in the foregoing method embodiments, and are not described herein again.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. An emergency shelter site selection and resource allocation method is characterized by comprising the following steps:
s1, classifying victims and emergency shelters according to the injury degree of the victims and the service level of the emergency shelters; seriously injured victims should be evacuated to a high-grade emergency shelter;
s2, on the premise that the condition that the victims of different grades are evacuated to the emergency shelters of different grades is met, constructing an emergency shelter site selection model by taking the total evacuation distance of all the victims and the total construction cost of all the selected emergency shelters as targets to evacuate the victims of different grades to the corresponding emergency shelters; the evacuation distance refers to the distance from a disaster point where disaster people are located to an emergency shelter to be evacuated;
s3, on the basis of the emergency refuge site selection model, constructing a resource distribution model by taking the total transportation cost of the resources and the total resource quantity of the unmet disaster residents as targets under the condition of considering insufficient total resource supply; the resources comprise living resources and medical resources, and the transportation cost refers to the cost for transporting the resources from the resource distribution center to each disaster people placement point; the disaster people placement point comprises: disaster-affected sites and various emergency shelters;
s4, determining a total model considering emergency shelter site selection and resource allocation at the same time based on the emergency shelter site selection model and the resource allocation model;
s5, solving the general model by adopting a simulated annealing algorithm and a particle swarm optimization algorithm, and determining the site selection and resource allocation scheme of the emergency shelter.
2. The method according to claim 1, wherein the step S1 specifically includes:
dividing the injury degree of the victims into the following parts according to a preset injury degree judgment standard: no injury, minor injury, and minor injury;
the emergency shelter is divided into a first-level emergency shelter and a second-level emergency shelter; the priority of the resources acquired by the primary emergency shelter is higher than that of the secondary emergency shelter; the service level provided by the primary emergency shelter is higher than that of the secondary emergency shelter;
wherein, the uninjured victims are arranged at the disaster-affected points of the victims, the slightly injured victims are arranged at the secondary emergency shelter, and the slightly injured victims are arranged at the primary emergency shelter.
3. The method of claim 2, wherein the emergency shelter addressing model comprises two objective functions:
Figure FDA0002255372760000021
Figure FDA0002255372760000022
objective function f1Means minimizing the total evacuation distance of all victims; dajRepresenting the distance from the disaster-affected point a to the primary refuge j; dakRepresenting the distance from the disaster-affected point a to the secondary shelter k;
Figure FDA0002255372760000023
the number of people evacuating from the disaster-affected point a to the first-level refuge j at the moment t is represented;
Figure FDA0002255372760000024
the number of people evacuating from the disaster-affected point a to a secondary refuge k at the moment t is represented;
objective function f2Represents minimizing the total construction cost of all selected emergency shelters; deltaj，Δk0 or 1, whereinj0 indicates that the primary refuge j is not selected, Δk0 indicates that the secondary shelter k is not selected, Δj1 indicates that the primary refuge j is selected, Δk1 indicates that the secondary shelter k is selected; cjRepresents the construction cost of the first-level shelter j, CkRepresents the construction cost of the secondary shelter k.
4. The method of claim 3, wherein the resource allocation model comprises two objective functions:
Figure FDA0002255372760000026
objective function f3Represents minimizing the total transportation cost of the resource; ctrRepresents a unit transportation cost per unit resource; dcj，Dck，DcaRespectively showing the distance from the distribution center c to a primary refuge j, a secondary refuge k and a disaster affected point a;
Figure FDA0002255372760000031
the quantity of the resources r conveyed from the distribution center c to the primary refuge j, the secondary refuge k and the disaster affected point a at the moment t is represented; omegaj，ωk，ωaRepresents the priority of resource demand points of three different levels, namely a first-level refuge j, a second-level refuge k and a disaster-affected point a, to the resource and omegaj+ωk+ωa＝1；
Objective function f4Represents the total number of resources that minimizes unmet disaster victims' needs;
Figure FDA0002255372760000032
Figure FDA0002255372760000033
respectively representing the quantity of the resources r which are not met by the primary refuge j, the secondary refuge k and the disaster-affected point a at the time t.
5. The method of claim 4, wherein said objective function that simultaneously considers an overall model of emergency shelter addressing and resource allocation comprises: f. of1、f4And f5；f5＝f2+f3。
6. The method according to claim 5, wherein the step S5 specifically comprises the steps of:
s51, adopting a simulated annealing algorithm to f1、f4And f5Selecting addresses of the emergency shelters of all levels as a target function so as to respectively place various victims and evacuate the corresponding victims to corresponding disaster-affected points or emergency shelters;
s52, adopting a particle swarm optimization algorithm to f3And f4And aiming at the target, resource allocation is carried out based on the site selection of the emergency shelter and the arrangement result of the disaster victims.
7. An emergency shelter site selection and resource allocation system, comprising:
the grade dividing unit is used for dividing the victims and the emergency refuges into grades according to the injury degree of the victims and the service level of the emergency refuges; seriously injured victims should be evacuated to a high-grade emergency shelter;
the site selection model determination unit is used for constructing an emergency refuge site selection model by taking the total evacuation distance of all the victims and the total construction cost of all the selected emergency refuges as targets to evacuate the victims of different grades to the corresponding emergency refuges on the premise of meeting the requirement that the victims of different grades are evacuated to the emergency refuges of different grades; the evacuation distance refers to the distance from a disaster point where disaster people are located to an emergency shelter to be evacuated;
a resource allocation model determining unit, configured to construct a resource allocation model with the goal of minimizing the total transportation cost of resources and minimizing the total resource quantity of unmet disaster victims' needs, in consideration of the situation that the total resource supply is insufficient, on the basis of the emergency shelter site selection model; the resources comprise living resources and medical resources, and the transportation cost refers to the cost for transporting the resources from the resource distribution center to each disaster people placement point; the disaster people placement point comprises: disaster-affected sites and various emergency shelters;
a general model determination unit, configured to determine, based on the emergency shelter site selection model and the resource allocation model, a general model that simultaneously considers emergency shelter site selection and resource allocation;
and the model solving unit is used for solving the total model by adopting a simulated annealing algorithm and a particle swarm optimization algorithm to determine the site selection and resource allocation scheme of the emergency shelter.
8. The system according to claim 7, wherein the ranking unit classifies the injury degree of the victims into: no injury, minor injury, and minor injury; the emergency shelter is divided into a first-level emergency shelter and a second-level emergency shelter; the priority of the resources acquired by the primary emergency shelter is higher than that of the secondary emergency shelter; the service level provided by the primary emergency shelter is higher than that of the secondary emergency shelter; wherein, the uninjured victims are arranged at the disaster-affected points of the victims, the slightly injured victims are arranged at the secondary emergency shelter, and the slightly injured victims are arranged at the primary emergency shelter.
9. The system of claim 8, wherein the emergency shelter addressing model comprises two objective functions:
Figure FDA0002255372760000041
Figure FDA0002255372760000042
objective function f1Means minimizing the total evacuation distance of all victims; dajRepresenting the distance from the disaster-affected point a to the primary refuge j; dakRepresenting the distance from the disaster-affected point a to the secondary shelter k;
Figure FDA0002255372760000051
the number of people evacuating from the disaster-affected point a to the first-level refuge j at the moment t is represented;
Figure FDA0002255372760000052
shows that people are evacuated from the disaster-affected point a to a secondary refuge k at the moment tCounting;
objective function f2Represents minimizing the total construction cost of all selected emergency shelters; deltaj，Δk0 or 1, whereinj0 indicates that the primary refuge j is not selected, Δk0 indicates that the secondary shelter k is not selected, Δj1 indicates that the primary refuge j is selected, Δk1 indicates that the secondary shelter k is selected; cjRepresents the construction cost of the first-level shelter j, CkRepresents the construction cost of the secondary shelter k.
10. The system of claim 9, wherein the resource allocation model comprises two objective functions:
Figure FDA0002255372760000053
objective function f3Represents minimizing the total transportation cost of the resource; ctrRepresents a unit transportation cost per unit resource; dcj，Dck，DcaRespectively showing the distance from the distribution center c to a primary refuge j, a secondary refuge k and a disaster affected point a;
Figure FDA0002255372760000055
the quantity of the resources r conveyed from the distribution center c to the primary refuge j, the secondary refuge k and the disaster affected point a at the moment t is represented; omegaj，ωk，ωaRepresents the priority of resource demand points of three different levels, namely a first-level refuge j, a second-level refuge k and a disaster-affected point a, to the resource and omegaj+ωk+ωa＝1；
Objective function f4Represents the total number of resources that minimizes unmet disaster victims' needs;
Figure FDA0002255372760000057
respectively representing the quantity of the resources r which are not met by the primary refuge j, the secondary refuge k and the disaster-affected point a at the time t.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114049756A (en) * 2022-01-14 2022-02-15 山东省计算中心（国家超级计算济南中心） Urban traffic emergency resource layout method and system

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101183445A (en) * 2007-12-20 2008-05-21 浙江大学 Personnel evacuation method for municipal traffic under calamity outburst surroundings
US20110087514A1 (en) * 2009-10-09 2011-04-14 International Business Machines Corporation Modeling distribution of emergency relief supplies for disaster response operations
CN102393925A (en) * 2011-07-05 2012-03-28 万达信息股份有限公司 Emergent vehicle scheduling and personnel evacuation method oriented to hazardous gas diffusion
CN105787595A (en) * 2016-02-29 2016-07-20 泰华智慧产业集团股份有限公司 Emergency logistic transfer station site selection method based on improved ant colony algorithm
CN107480853A (en) * 2017-07-05 2017-12-15 北京辰安信息科技有限公司 Goods and materials distribution method and goods and materials distributor
CN107507297A (en) * 2017-08-03 2017-12-22 鄂尔多斯市普渡科技有限公司 The countermeasure of traffic accident occurs for a kind of unmanned taxi
CN109993349A (en) * 2019-03-11 2019-07-09 同济大学 A kind of optimization method and device of city refuge addressing

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101183445A (en) * 2007-12-20 2008-05-21 浙江大学 Personnel evacuation method for municipal traffic under calamity outburst surroundings
US20110087514A1 (en) * 2009-10-09 2011-04-14 International Business Machines Corporation Modeling distribution of emergency relief supplies for disaster response operations
CN102393925A (en) * 2011-07-05 2012-03-28 万达信息股份有限公司 Emergent vehicle scheduling and personnel evacuation method oriented to hazardous gas diffusion
CN105787595A (en) * 2016-02-29 2016-07-20 泰华智慧产业集团股份有限公司 Emergency logistic transfer station site selection method based on improved ant colony algorithm
CN107480853A (en) * 2017-07-05 2017-12-15 北京辰安信息科技有限公司 Goods and materials distribution method and goods and materials distributor
CN107507297A (en) * 2017-08-03 2017-12-22 鄂尔多斯市普渡科技有限公司 The countermeasure of traffic accident occurs for a kind of unmanned taxi
CN109993349A (en) * 2019-03-11 2019-07-09 同济大学 A kind of optimization method and device of city refuge addressing

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114049756A (en) * 2022-01-14 2022-02-15 山东省计算中心（国家超级计算济南中心） Urban traffic emergency resource layout method and system
CN114049756B (en) * 2022-01-14 2023-06-06 山东省计算中心（国家超级计算济南中心） Urban traffic emergency resource layout method and system

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