CN107679650A - It is a kind of that the emergency materials method for optimizing scheduling rescued a little is had more towards how disaster-stricken point - Google Patents
It is a kind of that the emergency materials method for optimizing scheduling rescued a little is had more towards how disaster-stricken point Download PDFInfo
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Abstract
The invention discloses a kind of emergency materials method for optimizing scheduling for having more and being rescued a little towards how disaster-stricken point, this method consider emergency management and rescue during due to traffic congestion, weather, the influence of the uncertain factors such as road conditions, the uncertainty of haulage time is represented using interval number, establish the multi-objective Model for meeting " crash time is no more than the true degree maximum of crash time limitation and cost of transportation is minimum ", with confidence level highest and the minimum multiple target structure emergency materials Scheduling Optimization Model of cost, uniformity is not had based on confidence level and two targets of cost, introduce the derivation algorithm that ideal point proposes model, the ideal point sought between the two is optimal case, rescue the emergency materials intervention schedule problem of a little how disaster-stricken point to have more and provide method for solving.The inventive method, which solves, calculates simplicity, and required master data is easy to get, and energy aid decision making person determines rapidly rescue method after disaster occurs, and the rescue time of preciousness has been saved for emergency disaster relief action, has been with a wide range of applications.
Description
Technical Field
The invention relates to an emergency material scheduling optimization method for multiple disaster-receiving points and multiple rescue points, and belongs to the technical field of emergency material scheduling.
Background
Various sudden disasters and accidents form great threats to the development of human society and the safety of lives and properties of people, and sudden events generally have the characteristics of uncertainty, urgency and strong destructive power, and bring great loss to human beings once occurring. China is a country with frequent natural disasters, and in recent 10 years, the number of abnormal deaths and the number of disabilities of more than 20 ten thousand and more than 200 ten thousand caused by natural disasters, accident disasters, public health and social security events are more than 20 ten thousand every year on average. In order to reduce and reduce casualties and economic losses caused by emergencies as far as possible, the emergency scheduling problem of emergency supplies has important research significance.
In recent years, researchers have made intensive studies on the problem of transportation of emergency materials. For example, nolz and the like research the risk of transportation path interruption caused by infrastructure damage and resolve the problem into a multi-objective optimization problem; zheng and Ling put forward a multi-objective fuzzy optimization problem of emergency transportation planning, and a collaborative optimization method is developed; the Takeo Yamada converts the emergency problem into the solution of the shortest transportation path of the network, and further converts the emergency problem into the research of the network flow algorithm problem under the condition of the limitation of the road capacity; huang et al propose a successive approximation route evaluation method aimed at minimizing the total transportation time for relief supplies to the victim.
Some scholars combine the problem of emergency material transportation and the problem of site selection for research, for example, abonacer and the like take site selection transportation as a research view, consider that the selection of a transportation path depends on the number and the position of disaster area relief material distribution centers and the requirements of disaster victims, and establish a multi-target site selection-transportation model. Ghaffari-Nasab and the like calculate LRP through probabilistic transport time, and use different stochastic programming methods to provide some dual-target mathematical programming models, so that the overall cost of the system is reduced as much as possible, and meanwhile, the delivery time is expected to meet the minimum maximization principle.
In recent years, the problem of emergency material scheduling has been a major concern from time-based and cost-based multi-objective constrained planning. Some scholars have developed specific studies from the perspective of dispatch of relief supplies and personnel, post-disaster vehicle coordination, rescue-service dispatch, and the like. Some other scholars use case studies for qualitative analysis.
The above research is based on the assumption of deterministic requirements, but in practice, due to the burstiness and unpredictability of natural disasters, the requirements for saving materials are often very uncertain, and students have developed a series of researches on the problem of single-rescue-multiple-rescue-point under uncertain conditions according to the uncertain characteristics of the requirements. For the problem of multiple rescue points-single disaster-suffered points, the single-target problem, the two-stage problem and the multi-target problem which are shortest in time and minimum in rescue point number and the solving method thereof are researched by Liuchun forest and the like.
From the analysis, most students can research the relief material transportation and scheduling problems by establishing a quantitative model, the research relates to all angles, the research is relatively comprehensive, achievements of different degrees are obtained, the progress of emergency logistics material allocation research is promoted, but the research on the problem of material scheduling with more rescue points and more disaster-affected points in the problem of emergency material scheduling under an uncertain condition is less in related research, for example, ben-Tal and the like establish an optimal dynamic traffic distribution model based on a cell transmission model by expanding a robust optimization model so as to reduce risks brought by uncertainty of demand points in a relief supply chain; intensive research into systems is still required.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method is characterized by comprising the steps of establishing an emergency material scheduling optimization model by multiple targets with highest credibility and lowest cost and introducing a solution algorithm of an ideal point proposed model.
The invention adopts the following technical scheme for solving the technical problems:
an emergency material scheduling optimization method facing multiple disaster-receiving points and multiple rescue points comprises the following steps:
step 1, setting A i (i =1,2, \8230;, n) is the point of rescue, B j (j =1,2, \ 8230;, m) is the point of disaster, where each point of rescue is known to be for a certain point of rescueStoring quantity of emergency materials, knowing the demand of each disaster-receiving point for the emergency materials, knowing unit transportation cost from each rescue point to each disaster-receiving point, and adopting interval number to represent transportation time from the rescue point to the disaster-receiving point under the condition that the total quantity of the emergency materials of all the rescue points is more than or equal to the total demand of all the disaster-receiving points for the emergency materials, and establishing a multi-target model with the maximum fidelity and the minimum transportation cost, wherein the transportation time does not exceed an emergency time limit period;
step 2, respectively calculating a positive ideal point and a negative ideal point of an objective function P (Ψ, t) and C (Ψ) in the multi-objective model, wherein the P (Ψ, t) represents the scheduling task possibility degree of the scheme Ψ capable of completing the demand quantity of certain emergency materials at all disaster-affected points within an emergency time limit period t, and the C (Ψ) represents the transportation cost of the scheme Ψ;
step 3, solving each help-out point A according to the definition formula of the fidelity i To the disaster-affected point B j Is true ofThe obtained fidelityArranging a sequence in descending order, combining equivalent items in the sequence, deleting the items with the value of 0 in the sequence to obtain a sequence CF (k) (k =1,2, \ 8230;, L), wherein L is the number of elements contained in the sequence CF (k), and k =1;
step 4, orderSolving known rescue point A by using on-table operation method i (i =1,2, \8230;, n) emergency material inventory a 1 ,a 2 ,…,a n Known disaster site B j (j =1,2, \8230;, m) demand of emergency supplies b 1 ,b 2 ,…,b m The unit transportation cost is c' ij If the problem is solved, turning to step 5; if the problem is not feasible, turning to step 6;
step 5, calculating corresponding P (Ψ, t) and C (Ψ), and calculating a proximity value of the scheme Ψ to the ideal point by using a proximity formula;
step 6, let k = k +1, if k > L, the algorithm is terminated; otherwise, returning to the step 4;
step 7, if the algorithm is terminated and no feasible solution is obtained, indicating that the problem has no solution; otherwise, when the algorithm is terminated, the approach values corresponding to all feasible schemes are obtained, and the scheme with the maximum approach value is the optimal scheme.
As a preferred aspect of the present invention, the expression of the multi-objective model in which the transportation time does not exceed the emergency time limit, the fidelity is maximum, and the transportation cost is minimum in step 1 is as follows:
min C(Ψ)
z represents all feasible schemes, P (Ψ, t) represents the scheduling task possibility of the scheme Ψ for completing the demand quantity of some emergency materials of all disaster-affected points within an emergency time limit period t, C (Ψ) represents the transportation cost of the scheme Ψ, m is the number of all disaster-affected points, and P is the scheme corresponding to the jth disaster-affected pointThe number of the rescue points is included,presentation schemeThe time taken by each corresponding rescue point is not more than the fidelity of t,respectively represent the ith α 、i p From the rescue point to the jth disaster-receiving pointThe emergency materials for transportation are sent to the emergency personnel, respectively represent the ith α 、i p The unit transportation cost from the rescue point to the jth disaster-stricken point.
As a preferred embodiment of the present invention, the fidelity in step 3 is defined as follows:
wherein the content of the first and second substances,representing eventsThe degree of the process of (a) is,shows the rescue point A i To disaster-affected point B j The time of transportation of (a) is,respectively, the minimum value and the maximum value of the transportation time interval, and t is the emergency time limit period.
As a preferred solution of the present invention, the proximity formula in step 5 is as follows:
where ε is the proximity, ω 1 、ω 2 The weights of the scheme about the possibility degree and the rescue cost are respectively, P (psi, t) represents the possibility degree of the scheme psi for completing the scheduling task of all disaster-stricken points to some emergency material demand within the emergency time limit period t, C (psi) represents the transportation cost of the scheme psi, P(Ψ, t) is a positive ideal point and a negative ideal point of P (Ψ, t), respectively, C(Ψ) is a positive ideal point and a negative ideal point of C (Ψ), respectively.
As a preferred scheme of the invention, the scheme is related to the weight omega of the possibility degree and the rescue cost 1 、ω 2 The values are 0.8 and 0.2 respectively.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
1. the invention considers the influence of uncertain factors such as traffic jam, weather, road conditions and the like in the emergency rescue process, adopts the interval number to express the uncertainty of the transportation time, researches the emergency material emergency scheduling problem of multiple rescue points-multiple disaster points under the condition of uncertain rescue time, establishes a multi-target model meeting the requirements that the emergency time is not more than t, the fidelity is maximum and the transportation cost is minimum, and provides a corresponding solving method, thereby providing a solving scheme for the emergency material emergency scheduling problem of the multiple rescue points-multiple disaster points.
2. The algorithm is simple and convenient to solve and calculate, the needed basic data is easy to obtain, and a decision maker can be helped to quickly determine the rescue scheme after a disaster occurs, so that precious rescue time is saved for emergency disaster relief actions.
Detailed Description
The following detailed description describes embodiments of the invention, which are exemplary only and are not to be construed as limiting the invention.
The invention relates to an emergency material scheduling optimization method facing multiple disaster-receiving points and multiple rescue points, which comprises the following specific processes:
1. description of the problems
Suppose A 1 ,A 2 ,…,A n N points of rescue, B 1 ,B 2 ,…,B m Is m disaster-affected points, each rescue point A i (i =1,2, \8230;, n) the stock of a certain material is a 1 ,a 2 ,…,a n Each disaster point B j (j =1,2, \8230;, m) the demand for this kind of material is b 1 ,b 2 ,…,b m And the material holding amount of the rescue point can meet the material demand amount of the disaster-stricken point, that is
Due to the fact that the person goes out of the rescue point A i Transporting materials to disaster-stricken site B j The transportation time is uncertain due to the influence of uncertain factors such as traffic jam, weather, road conditions and the like, and the number of the used sections isThe emergency time limit period is t, and the transportation unit cost is c ij . The decision objective of the optimal scheme in the invention is to maximize the scheme fidelity with the emergency time not exceeding t and minimize the transportation cost under the condition of meeting the material requirement.
2. Construction of models
2.1 model assumptions
The model of the invention is based on the following assumptions:
(1) In the transportation process, due to the influence of uncertain factors such as traffic jam, weather, road conditions and the like, uncertainty of transportation time is represented by the number of sections;
(2) The unit transportation cost from each rescue point to each disaster-receiving point is a determined number;
(3) The emergency material demand of all disaster-affected points under different disaster grades is known;
(4) The total supply amount of the materials at all rescue points can meet the material requirements of all disaster-stricken points.
2.2 model construction
Since the emergency time is limited to t, the concept of fidelity is introduced, andrepresenting eventsThe certainty factor(s) can avoid the situation that the solution with the emergency time not exceeding t does not exist. From the description of the above problem, define:
when in useWhen the utility model is used, the water is discharged,degradation is real, defining:
by usingPresentation scheme(scheme (I)P rescue points) can complete the disaster-affected point B within the emergency time limit period t j Demand for certain goods and materials b j Is scheduled toThe service availability is as followsMeans "schemeThe minimum value of the fidelity of the event that the time taken by each corresponding rescue point is not more than t' is the possibility that the scheduling task can be completed. Using fuzzy reasoning, we can obtain:
scheme represented by P (psi, t)The scheduling task possibility of all disaster-affected points on the demand of certain goods and materials can be completed within the emergency time limit period t, namelyAll feasible solution sets are represented by Z, the solution objective of the invention is to find out the solution with the maximum possibility in Z, and the rescue cost is minimized on the basis, and the cost of the solution psi is represented by C (psi), and the model can be established as follows:
min C(Ψ)
3. solving algorithm of model
This is a typical multi-objective planning problem, and the solution here adopts the method of ideal points: respectively calculating positive ideal points of target functions P (psi, t) and C (psi)And negative ideal pointP(Ψ, t) and C (Ψ), and then calculating the size of the proximity epsilon according to the formula (5), and determining the relative proximity of each feasible scheme Ψ to the ideal point, wherein the larger epsilon indicates the better scheme. So far, the multi-objective problem of the original problem translates into a problem of finding the maximum closeness.
ω 1 And ω 2 The weights of the feasible solution with respect to the probability and the cost of rescue are given by experts, and ω is 1 +ω 2 ＝1。
3.1 evaluation of Positive and negative ideal points of the objective function
Firstly, the first step is toObtaining a group of descending sequence according to the descending sequenceWherein p is a seriesTo the required quantity b j (j =1,2, \8230;, m). Order:
at this time, the emergency completion time corresponding to the scheme Ψ' does not exceed the maximum possible degree of the emergency limit time t, and the positive ideal point of the objective function P (Ψ, t) isCorrespondingly willThe negative ideal point of the objective function is obtained according to ascending order from small to large
For the same reason, the sequence a 1j ,a 2j ,…,a nj According to c ij (i =1,2, \8230;, n) in ascending order of magnitude, giving a completely new set of seriesWherein q is a sequence of numbersFor the required quantity b j (j =1,2, \8230;, m). Order to
The rescue cost corresponding to the scheme psi' is lowest, i.e.In the same way, the sequence a 1j ,a 2j ,…,a nj According to the cost c ij The descending order of the sizes of (i =1,2, \8230;, n) can obtain the scheme with the highest rescue cost, and the negative ideal point of C (psi) is obtainedC(Ψ)。
3.2 solving of feasible solutions
If P (Ψ, t) =0 for a solution, it means that the solution is not feasible; if P (Ψ, t) >0 of the solution, it means that the solution is feasible; if P (Ψ, t) >0 of the solution does not exist, no feasible solution is represented.
3.3 Algorithm Steps
(1) Calculating a positive ideal point and a negative ideal point;
(2) Firstly, the truth of each rescue point i to the disaster point j is solved according to the truth definition formula (1)The obtained fidelityArranging the data into a sequence in descending order, combining the equivalent items in the sequence, deleting the items which are 0 in the sequence to obtain a sequence CF (k) (k =1,2, \ 8230l) and letting k =1;
(3) Order toAsk for help A i (i =1,2, \8230;, n) stock of material is a 1 ,a 2 ,…,a n Point of disaster B j (j =1,2, \8230;, m) the required amount of material is b 1 ,b 2 ,…,b m Unit transportation cost is c i ′ j The transportation problem of minimized transportation cost belongs to the problem of classical operational research and can be solved by using a table-top operation method; if the problem has a solution, turning to (4); if the problem has no feasible solution, directly turning to (5);
(4) Computing correspondencesAndsolving the epsilon value corresponding to each feasible scheme by using a formula (5);
(5) Let k = k +1, if k > L, the algorithm terminates; otherwise, returning to the step (3);
through the calculation, if the problem has no feasible solution, the problem is represented to have no solution; otherwise, the epsilon value corresponding to each feasible scheme is solved, and the scheme with the maximum epsilon value is the optimal scheme according to the definition of the ideal point.
4. Detailed description of the preferred embodiments
The existing three disaster-stricken points have the requirements of certain emergency materials b 1 ＝70、b 2 ＝80、b 3 The transport problem is planned and solved by using the LINDO 9.0, wherein the transport problem is solved by using CF (k) = (1, 0.8,0.75,0.714,0.667,0.6,0.5 and 0.4), and the calculation process and the result are shown in the table 2.
TABLE 1 known data from rescue points to disaster points
TABLE 2 calculation procedures and results
As can be seen from table 2, it is, P(Ψ,t)＝0.4， C(Ψ) =2446, and since time is much more important than emergency dispatch cost for emergency rescue when an emergency disaster occurs, ω is taken 1 ＝0.8，ω 2 =0.2, and epsilon is obtained by calculating epsilon corresponding to each scheme 2 ＝0.6411，ε 3 ＝0.6195，ε 4 ＝0.6044，ε 5 ＝0.5927，ε 6 ＝0.5518，ε 7 ＝0.4811，ε 8 =0.3969, so when k =2, the corresponding schemeThe optimal scheme is as follows: a. The 1 、A 2 、A 3 The materials coming out of the rescue point are conveyed to the station B 1 Point, A 1 、A 8 Point goods and materials are conveyed to B 2 Point, A 3 、A 5 、A 7 Point goods and materials are conveyed to B 3 And (4) point.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.
Claims (5)
1. A multi-disaster-point-multi-rescue-point oriented emergency material scheduling optimization method is characterized by comprising the following steps:
step 1, setting A i (i =1,2, \8230;, n) is the point of rescue, B j (j =1,2, \ 8230;. M) is a disaster-suffering point, under the condition that the stock of certain emergency materials of each rescue point is known, the demand of each disaster-suffering point for the emergency materials is known, the unit transportation cost from each rescue point to each disaster-suffering point is known, and the total stock of the emergency materials of all the rescue points is greater than or equal to the total demand of all the disaster-suffering points for the emergency materials, the transportation time from the emergency materials to the disaster-suffering points is represented by adopting interval numbers, and a multi-target model with the maximum fidelity and the minimum transportation cost and the transportation time not exceeding the emergency time limit period is established;
step 2, respectively calculating a positive ideal point and a negative ideal point of an objective function P (Ψ, t) and C (Ψ) in the multi-objective model, wherein the P (Ψ, t) represents the scheduling task possibility degree of the scheme Ψ capable of completing the demand quantity of certain emergency materials at all disaster-affected points within an emergency time limit period t, and the C (Ψ) represents the transportation cost of the scheme Ψ;
step 3, solving each help-out point A according to the definition formula of the fidelity i To disaster-affected point B j Is true ofThe obtained fidelityArranging a sequence in descending order, combining equivalent items in the sequence, deleting the items with the value of 0 in the sequence to obtain a sequence CF (k) (k =1,2, \ 8230;, L), wherein L is the number of elements contained in the sequence CF (k), and k =1;
step 4, orderSolving known rescue point A by using on-table operation method i (i =1,2, \8230;, n) emergency material stock a 1 ,a 2 ,…,a n Known disaster-affected site B j (j =1,2, \8230;, m) demand amount b of emergency supplies 1 ,b 2 ,…,b m The unit transportation cost is c' ij If the problem is solved, turning to step 5; if the problem is not feasible, turning to step 6;
step 5, calculating corresponding P (Ψ, t) and C (Ψ), and calculating a proximity value of the scheme Ψ to the ideal point by using a proximity formula;
step 6, let k = k +1, if k > L, the algorithm is terminated; otherwise, returning to the step 4;
step 7, if the algorithm is terminated and no feasible solution is obtained, indicating that the problem has no solution; otherwise, when the algorithm is terminated, the approach values corresponding to all feasible schemes are obtained, and the scheme with the maximum approach value is the optimal scheme.
2. The method for scheduling and optimizing emergency materials for multiple disaster-affected points and multiple rescue points according to claim 1, wherein the expression of the multi-objective model with the largest true transportation time not exceeding the emergency time limit and the smallest transportation cost in step 1 is as follows:
minC(Ψ)
z represents all feasible schemes, P (Ψ, t) represents the scheduling task possibility of the scheme Ψ for completing the demand quantity of some emergency materials of all disaster-affected points within an emergency time limit period t, C (Ψ) represents the transportation cost of the scheme Ψ, m is the number of all disaster-affected points, and P is the scheme corresponding to the jth disaster-affected pointThe number of the rescue points contained in the rescue system,presentation schemeThe time used by each corresponding rescue point is not more than the fidelity of t,respectively represent the ith α 、i p Emergency materials delivered by the rescue point to the jth disaster-stricken point, respectively represent the ith α 、i p The unit transportation cost from the rescue point to the jth disaster-stricken point.
3. The method for scheduling and optimizing emergency materials for multiple disaster-affected points and multiple rescue points according to claim 1, wherein the fidelity definition in step 3 is as follows:
wherein, the first and the second end of the pipe are connected with each other,representing eventsThe degree of the process of (a) is,shows the rescue point A i To the disaster-affected point B j The time of transportation of (a) is,respectively, the minimum value and the maximum value of the transportation time interval, and t is the emergency time limit period.
4. The method for scheduling and optimizing emergency materials for multiple disaster-relief points according to claim 1, wherein the proximity formula in step 5 is as follows:
where ε is the proximity, ω 1 、ω 2 Respectively, the weight of the scheme about the possibility and the rescue cost, P (Ψ, t) represents the possibility of the scheme Ψ for completing the scheduling task of all disaster points to some emergency material demand within the emergency time limit period t, C (Ψ) represents the transportation cost of the scheme Ψ, P(Ψ, t) is a positive ideal point of P (Ψ, t), respectivelyAnd a negative ideal point, wherein the negative ideal point is a point, C(Ψ) is a positive ideal point and a negative ideal point of C (Ψ), respectively.
5. The method for optimizing the dispatching of emergency materials for multiple disaster-relief points according to claim 4, wherein the weight ω of the scheme with respect to the probability and the cost of rescue 1 、ω 2 The values are 0.8 and 0.2 respectively.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109711764A (en) * | 2018-11-28 | 2019-05-03 | 国网信息通信产业集团有限公司北京分公司 | A kind of power emergency materials measurement method and device |
| CN110020778A (en) * | 2019-02-21 | 2019-07-16 | 国网山东省电力公司临沂供电公司 | The power emergency distribution of materials and configuration system and method |
| CN110619431A (en) * | 2019-09-17 | 2019-12-27 | 浙江树人学院（浙江树人大学） | Vehicle transportation scheduling method for flood prevention rescue goods and materials in disaster relief |
| CN110782087A (en) * | 2019-10-24 | 2020-02-11 | 大连海事大学 | Offshore emergency material optimal scheduling method and system |
| CN111126682A (en) * | 2019-12-13 | 2020-05-08 | 中国民用航空飞行学院 | Navigation rescue scheduling optimization method based on rescue efficiency |
| CN111160649A (en) * | 2019-12-30 | 2020-05-15 | 北京邮电大学 | Resource scheduling scheme obtaining method and device |
| CN111626545A (en) * | 2020-04-06 | 2020-09-04 | 合肥工业大学 | Emergency rescue material high-dimensional multi-target distribution method and system |
| CN112001547A (en) * | 2020-08-24 | 2020-11-27 | 天津大学 | Rock-fill dam earth and stone allocation optimization method based on improved interval multi-objective optimization |
| CN112257946A (en) * | 2020-10-29 | 2021-01-22 | 中国人民解放军空军工程大学 | Equipment transportation multi-objective optimization model in emergency state |
| CN112990577A (en) * | 2021-03-16 | 2021-06-18 | 昆明理工大学 | Mine accident emergency rescue dynamic scheduling modeling method integrating demand satisfaction and disaster victims loss |
| CN113159700A (en) * | 2021-01-19 | 2021-07-23 | 昆明理工大学 | Convergence demand prediction accident emergency material scheduling modeling method for mine emergency rescue central station |
| CN113705970A (en) * | 2021-07-28 | 2021-11-26 | 北京联合大学 | HTN planning method for emergency logistics resource task matching |
| CN113887946A (en) * | 2021-09-30 | 2022-01-04 | 煤炭科学研究总院 | Emergency material transportation scheduling method and device for hydrogen energy driven non-stop transmission and storage medium |
| CN113962596A (en) * | 2021-11-10 | 2022-01-21 | 应急管理部国家减灾中心 | Method and device for generating intelligent emergency material allocation scheme |
| CN113962481A (en) * | 2021-11-15 | 2022-01-21 | 北京市应急管理科学技术研究院 | Resource allocation method and device for emergency materials and server |
| CN114707770A (en) * | 2022-06-06 | 2022-07-05 | 中国民航大学 | Aviation emergency rescue decision optimization method based on rescue timeliness |
| CN115907238A (en) * | 2023-02-27 | 2023-04-04 | 南京邮电大学 | Multi-target emergency material center site selection method based on improved prey optimization algorithm |
| CN116362392A (en) * | 2023-03-21 | 2023-06-30 | 江陵县百顺通达物流有限公司 | Material scheduling and carrying method, equipment and computer storage medium |
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| CN109711764A (en) * | 2018-11-28 | 2019-05-03 | 国网信息通信产业集团有限公司北京分公司 | A kind of power emergency materials measurement method and device |
| CN110020778A (en) * | 2019-02-21 | 2019-07-16 | 国网山东省电力公司临沂供电公司 | The power emergency distribution of materials and configuration system and method |
| CN110619431A (en) * | 2019-09-17 | 2019-12-27 | 浙江树人学院（浙江树人大学） | Vehicle transportation scheduling method for flood prevention rescue goods and materials in disaster relief |
| CN110619431B (en) * | 2019-09-17 | 2022-03-25 | 浙江树人学院（浙江树人大学） | Vehicle transportation scheduling method for flood prevention rescue goods and materials in disaster relief |
| CN110782087B (en) * | 2019-10-24 | 2023-08-25 | 大连海事大学 | Offshore emergency material optimal scheduling method and system |
| CN110782087A (en) * | 2019-10-24 | 2020-02-11 | 大连海事大学 | Offshore emergency material optimal scheduling method and system |
| CN111126682A (en) * | 2019-12-13 | 2020-05-08 | 中国民用航空飞行学院 | Navigation rescue scheduling optimization method based on rescue efficiency |
| CN111126682B (en) * | 2019-12-13 | 2022-03-15 | 中国民用航空飞行学院 | Navigation rescue scheduling optimization method based on rescue efficiency |
| CN111160649A (en) * | 2019-12-30 | 2020-05-15 | 北京邮电大学 | Resource scheduling scheme obtaining method and device |
| CN111160649B (en) * | 2019-12-30 | 2023-07-21 | 北京邮电大学 | Resource scheduling scheme acquisition method and device |
| CN111626545A (en) * | 2020-04-06 | 2020-09-04 | 合肥工业大学 | Emergency rescue material high-dimensional multi-target distribution method and system |
| CN111626545B (en) * | 2020-04-06 | 2022-11-04 | 合肥工业大学 | Emergency rescue material high-dimensional multi-target distribution method and system |
| CN112001547A (en) * | 2020-08-24 | 2020-11-27 | 天津大学 | Rock-fill dam earth and stone allocation optimization method based on improved interval multi-objective optimization |
| CN112001547B (en) * | 2020-08-24 | 2023-01-10 | 天津大学 | Rock-fill dam earth-rock allocation optimization method based on improved interval multi-objective optimization |
| CN112257946A (en) * | 2020-10-29 | 2021-01-22 | 中国人民解放军空军工程大学 | Equipment transportation multi-objective optimization model in emergency state |
| CN112257946B (en) * | 2020-10-29 | 2023-05-30 | 中国人民解放军空军工程大学 | Multi-objective optimization model for equipment transportation in emergency state |
| CN113159700A (en) * | 2021-01-19 | 2021-07-23 | 昆明理工大学 | Convergence demand prediction accident emergency material scheduling modeling method for mine emergency rescue central station |
| CN112990577B (en) * | 2021-03-16 | 2022-07-26 | 昆明理工大学 | Mine accident emergency rescue dynamic scheduling modeling method integrating demand satisfaction and disaster victims loss |
| CN112990577A (en) * | 2021-03-16 | 2021-06-18 | 昆明理工大学 | Mine accident emergency rescue dynamic scheduling modeling method integrating demand satisfaction and disaster victims loss |
| CN113705970A (en) * | 2021-07-28 | 2021-11-26 | 北京联合大学 | HTN planning method for emergency logistics resource task matching |
| CN113887946A (en) * | 2021-09-30 | 2022-01-04 | 煤炭科学研究总院 | Emergency material transportation scheduling method and device for hydrogen energy driven non-stop transmission and storage medium |
| CN113887946B (en) * | 2021-09-30 | 2022-07-26 | 煤炭科学研究总院有限公司 | Emergency material transportation scheduling method and device driven by hydrogen energy and transmitted without stopping |
| CN113962596A (en) * | 2021-11-10 | 2022-01-21 | 应急管理部国家减灾中心 | Method and device for generating intelligent emergency material allocation scheme |
| CN113962481A (en) * | 2021-11-15 | 2022-01-21 | 北京市应急管理科学技术研究院 | Resource allocation method and device for emergency materials and server |
| CN114707770A (en) * | 2022-06-06 | 2022-07-05 | 中国民航大学 | Aviation emergency rescue decision optimization method based on rescue timeliness |
| CN115907238A (en) * | 2023-02-27 | 2023-04-04 | 南京邮电大学 | Multi-target emergency material center site selection method based on improved prey optimization algorithm |
| CN116362392A (en) * | 2023-03-21 | 2023-06-30 | 江陵县百顺通达物流有限公司 | Material scheduling and carrying method, equipment and computer storage medium |
| CN116362392B (en) * | 2023-03-21 | 2024-05-10 | 北京神州数码云科信息技术有限公司 | Material scheduling and carrying method, equipment and computer storage medium |
| CN117455211A (en) * | 2023-12-26 | 2024-01-26 | 济南大学 | Cross-regional scheduling method and system for emergency materials, electronic equipment and storage medium |
| CN117455211B (en) * | 2023-12-26 | 2024-03-15 | 济南大学 | Cross-regional scheduling method and system for emergency materials, electronic equipment and storage medium |
| CN117745042A (en) * | 2024-02-20 | 2024-03-22 | 广东省科技基础条件平台中心 | Multi-disaster-point emergency material scheduling method, device, medium and equipment |
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