CN108280575A - A kind of multiple batches of scheduling decision method of emergency evacuation vehicle - Google Patents
A kind of multiple batches of scheduling decision method of emergency evacuation vehicle Download PDFInfo
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Abstract
The invention discloses a kind of multiple batches of scheduling decision methods of emergency evacuation vehicle so that disaster affected people is quickly and efficiently evacuated to appointed place to solve multiple batches of vehicle dispatching problem when especially emergency vehicles are in short supply under emergency condition.The system includes data input module, data calculation processing module and scheme output module.Data input includes static data：Evacuate website and parking lot geographical location, parking lot to each website shortest path, emergency vehicles sum and the input and storage of capacity and the input of real time data.Data calculation processing module is by building vehicle scheduling mathematical model and utilizing the generation of non-dominated ranking Global Genetic Simulated Annealing Algorithm realization vehicle scheduling scheme.Scheme output module reprocesses the numerical solution that system-computed obtains, and code is converted into word and exports corresponding route scheme.The present invention is suitable for road traffic contingency management field, improves emergency response speed, while keeping emergency vehicles scheduling process easier, rapid, effective.
Description
Technical field
The present invention relates to a kind of multiple batches of scheduling decision methods of emergency evacuation vehicle.
Background technology
With the development of Chinese national economy and the continuous propulsion of urbanization process, resident's car ownership year by year on
It rises, road traffic accident frequently occurs therewith.At the same time, accidental pollution event, major event also have normal traffic function
Very big influence, or even can induce second accident, impacts range bigger, duration longer harm.According to traffic accident injury
Person investigates display, and China, which rides in ambulances, to be reached the wounded for being given treatment to of hospital and only about account for 14.3%.Related accidents statistical number
According to show if accident occur 5 minutes in use emergency relief measure, emergency call salving, at least 18%- are carried out in 30 minutes
25% heavy the wounded can be from death；And if the wounded can obtain medical treatment after 30 minutes, dead risk
Increase 3 times.Based on this background, road traffic accident is emergent, is damaged for caused by reducing traffic accident and Disaster Event
It loses, ensure that people's life and property safety, or even the aspect of stablizing of society all play a crucial role, it is necessary to give enough
Concern and attention.
Emergency management and rescue evacuation relies on road traffic system, and redundant labor transfer is required for having come by vehicle with goods and materials allotment
At, therefore vehicle scheduling process is the key link of road traffic contingency management, and transport task is only rationally assigned for vehicle, is closed
Programme path is managed, could ensure that rescue evacuation is unfolded in the best opportunity, reduce unnecessary loss.
In previous emergency vehicles scheduling strategy, generally it converts the scheduling problem of emergency vehicles on traditional vehicle road
Diameter problem (Vehicle Routing Problem, VRP), the scheme obtained fails to fully consider that emergency vehicles are in short supply mostly
Under the conditions of multiple batches of vehicle scheduling and demand to each customer rs site the case where splitting.Meanwhile it is existing in relation to answering
The research of anxious vehicle scheduling is typically limited to theoretic, lack it is a kind of effectively can practical application emergency vehicles scheduling auxiliary
Decision-making technique.
Invention content
Based on the above shortcoming, the present invention provides a kind of emergency evacuation vehicle scheduling in road traffic contingency management field
Decision-making technique, relief road traffic administration person solves multiple batches of vehicle tune when especially emergency vehicles are in short supply under emergency condition
Degree problem improves emergency response speed, and enables disaster affected people by rapidly and efficiently by generating reasonable efficient scheduling scheme
Ground is evacuated to appointed place, is lost caused by reducing burst fire-disaster event.
The technical solution adopted in the present invention：A kind of multiple batches of scheduling decision method of emergency evacuation vehicle, including data are defeated
Enter module, data processing module and data outputting module, method is specific as follows：
The data input module includes static and dynamic data input, storage and calling, and static data includes：It dredges
Dissipate website and parking lot geographical location, area road network, the road grid traffic flow of historical statistics, parking lot to each website shortest path
Diameter, emergency vehicles sum and capacity, static data need to be previously entered system and store, in case to it when vehicle route schemes generation
It is called；Wherein, the magnitude of traffic flow of the transit time in section based on section calculated using BPR functions, parking lot to each station
Point transit time of the shortest path based on road network and section is calculated using Dijkstra's algorithm；Dynamically data include：
Each website waits for that number of evacuation, the damage situation of road network, the real-time traffic flow data in each section, system can be according to the dynamics of input
Data are updated and supplement to static data, including the damage of certain section then updates connectivity data, the section of road network in road network
The magnitude of traffic flow variation its transit time is then updated according to BPR functions；
BPR function formulas are：
In formula：
T --- pass through the real time in section；
t0--- the free running time in section；
The volume of traffic in q --- section, unit pcu/h；
The actual capacity in C --- section, unit pcu/h；
α, β are model undetermined parameter, α=0.15, β=4；
The data processing module function is the side that the data based on data input module generate the multiple batches of scheduling of vehicle
Case, first according to emergency evacuation the characteristics of, establish the target dispatch model of emergency evacuation vehicle, target dispatch model includes：Most
Smallization total deadline minimizes the average arrival time for waiting for evacuation personnel；
The minimum total deadline, i.e. target one are as follows：
In formula：--- the time of v transport task before vehicle k is completed, k index for vehicle, and maximum value m, v are the range of driving
Index, maximum value NMT；
Described minimizes the average arrival time for waiting for evacuation personnel, i.e. target two is as follows：
In formula：
--- decision variable, during vehicle k takes action at its v times, in the number that website i is carried, i is site number rope
Draw, i=0,1,2 ... n, 0 numbers for sanctuary；
R --- total number of persons to be evacuated；
Wherein, constraints is as follows：
In formula：--- decision variable during vehicle k takes action at its v times, by arc (i, j), is to take 1, otherwise takes 0；
tij--- the running time between website i and j；
Q --- emergency vehicles maximum capacity；
si--- wait for number of evacuation at emergent website i；
The meaning of constraints is respectively：The calculating of vehicle travel time, each site traffic conservation, vehicle one way deliver people
Number limitation, all personnel is both needed to be evacuated, vehicle must could service it by way of certain website；
Secondly, mathematical model is asked using quick non-dominated ranking algorithm, genetic algorithm, enhanced simulated annealing
Solution, different scheduling schemes is ranked up according to the relative importance of object function using quick non-dominated ranking algorithm and
Grade classification, and by target one as the Main Basiss to solution sequence, target two is used as secondary foundation；It is carried out by genetic algorithm
Generation, screening, the optimization of route scheme, and in genetic algorithm iterative process, at interval of certain iterations, utilize improvement
Simulated annealing to current optimal solution re-optimization, improve the local search ability of algorithm；Finally, according to the demand of policymaker
Or the end condition of algorithm terminates to calculate, and obtains corresponding vehicle scheduling scheme；
Wherein, when carrying out the gene code of genetic algorithm, the length of coding is N × m × q,
N is the maximum times that each vehicle can take action, and m is the sum of vehicle, and q is bicycle capacity, by every disaster-stricken people
Member is regarded as a basic gene point, and is represented using the point serial number residing for it, then has R website member in each encoding
Element and N × m × q-R occupy-place element, R is total number of persons, from the front to the back per continuous q element represent certain vehicle certain take action
Delivery and route plan, the sequence occurred according to site element in q element are determined to its access order, according to site element
Quantity determine the point handling capacity of passengers, selection, variation, intersect etc. genetic operators using quick non-dominated ranking heredity calculation
Method；Simultaneously to improve local search efficiency, in an iterative process, an enhanced simulated annealing is called every certain algebraically
Local optimum search is carried out, enhanced simulated annealing formula is：
In formula：The new solution that P --- simulated annealing searches replaces the probability solved originally；
--- i-th of desired value of new explanation；
--- i-th of desired value of original solution；
α --- the constant between 0 to 1；
This called iterations of n --- simulated annealing；
The data outputting module function is that the numerical solution that data processing module generates is converted and exported, and is exported
Content includes：Number, each vehicle of each vehicle action are taken action the evacuation station number and sequence, each row of each vehicle of process every time
The number carried in each evacuation website is moved, other data of output further include：The distance of each vehicle traveling, each vehicle driver are pre-
Count the working time, each object function result of calculation：Evacuate movable total deadline, when the average arrival of evacuation personnel
Between, all vehicles traveling total distance, in case decision-maker checks inspection.
Advantages of the present invention and advantageous effect：The present invention considers vehicle and repeatedly takes action and split to website demand
Condition more meets the actual needs of emergency vehicles management and running；The algorithm computational efficiency height of design, stability are strong, can ensure
The feasibility and validity of the timeliness of emergency response and generated scheme；This system structure is simplified easily operated, is compensated for
The vacancy of road emergency traffic management auxiliary tool, reduces the requirement to the knowledge and technology of control of traffic and road person, makes to meet an urgent need
Vehicle scheduling process is concisely efficient.The present invention improves emergency response speed, while keeping emergency vehicles scheduling process easier, fast
It is fast, effective.
Description of the drawings
Fig. 1 is the system structure diagram of the present invention；
Fig. 2 is this system workflow schematic diagram.
Specific implementation mode
Embodiment 1
As shown in Figs. 1-2, a kind of multiple batches of scheduling decision method of emergency evacuation vehicle, including data input module, data
Processing module and data outputting module are as follows：
The data input module includes static and dynamic data input, storage and calling, and static data includes：It dredges
Dissipate website and parking lot geographical location, area road network, the road grid traffic flow of historical statistics, parking lot to each website shortest path
Diameter, emergency vehicles sum and capacity, static data need to be previously entered system and store, in case to it when vehicle route schemes generation
It is called；Wherein, the magnitude of traffic flow of the transit time in section based on section calculated using BPR functions, parking lot to each station
Point transit time of the shortest path based on road network and section is calculated using Dijkstra's algorithm；Dynamically data include：
Each website waits for that number of evacuation, the damage situation of road network, the real-time traffic flow data in each section, system can be according to the dynamics of input
Data are updated and supplement to static data, including the damage of certain section then updates connectivity data, the section of road network in road network
The magnitude of traffic flow variation its transit time is then updated according to BPR functions；
BPR function formulas are：
In formula：
T --- pass through the real time in section；
t0--- the free running time in section；
The volume of traffic in q --- section, unit pcu/h；
The actual capacity in C --- section, unit pcu/h；
α, β are model undetermined parameter, α=0.15, β=4；
The data processing module function is the side that the data based on data input module generate the multiple batches of scheduling of vehicle
Case；First according to emergency evacuation the characteristics of, the target dispatch model of emergency evacuation vehicle is established, target dispatch model includes：Most
Smallization total deadline minimizes the average arrival time for waiting for evacuation personnel；
The minimum total deadline, i.e. target one are as follows：
In formula：--- the time of v transport task before vehicle k is completed, k index for vehicle, and maximum value m, v are the range of driving
Index, maximum value NMT；
Described minimizes the average arrival time for waiting for evacuation personnel, i.e. target two is as follows：
In formula：
--- decision variable, during vehicle k takes action at its v times, in the number that website i is carried, i is site number rope
Draw, i=0,1,2 ... n, 0 numbers for sanctuary；
R --- total number of persons to be evacuated；
Wherein, constraints is as follows：
In formula：--- decision variable during vehicle k takes action at its v times, by arc (i, j), is to take 1, otherwise takes 0；
tij--- the running time between website i and j；
Q --- emergency vehicles maximum capacity；
si--- wait for number of evacuation at emergent website i；
The meaning of constraints is respectively：The calculating of vehicle travel time, each site traffic conservation, vehicle one way deliver people
Number limitation, all personnel is both needed to be evacuated, vehicle must could service it by way of certain website；
Secondly, mathematical model is asked using quick non-dominated ranking algorithm, genetic algorithm, enhanced simulated annealing
Solution, different scheduling schemes is ranked up according to the relative importance of object function using quick non-dominated ranking algorithm and
Grade classification, and by target one as the Main Basiss to solution sequence, target two is used as secondary foundation；It is carried out by genetic algorithm
Generation, screening, the optimization of route scheme, and in genetic algorithm iterative process, at interval of certain iterations, utilize improvement
Simulated annealing to current optimal solution re-optimization, improve the local search ability of algorithm；Finally, according to the demand of policymaker
Or the end condition of algorithm terminates to calculate, and obtains corresponding vehicle scheduling scheme；
Wherein, when carrying out the gene code of genetic algorithm, the length of coding is N × m × q,
N is the maximum times that each vehicle can take action, and m is the sum of vehicle, and q is bicycle capacity, by every disaster-stricken people
Member is regarded as a basic gene point, and is represented using the point serial number residing for it, then has R website member in each encoding
Element and N × m × q-R occupy-place element, R is total number of persons, from the front to the back per continuous q element represent certain vehicle certain take action
Delivery and route plan, the sequence occurred according to site element in q element are determined to its access order, according to site element
Quantity determine the point handling capacity of passengers, selection, variation, intersect etc. genetic operators using quick non-dominated ranking heredity calculation
Method；Simultaneously to improve local search efficiency, in an iterative process, an enhanced simulated annealing is called every certain algebraically
Local optimum search is carried out, enhanced simulated annealing formula is：
In formula：The new solution that P --- simulated annealing searches replaces the probability solved originally；
--- i-th of desired value of new explanation；
--- i-th of desired value of original solution；
α --- the constant between 0 to 1；
This called iterations of n --- simulated annealing；
The data outputting module function is that the numerical solution that data processing module generates is converted and exported, and is exported
Content includes：Number, each vehicle of each vehicle action are taken action the evacuation station number and sequence, each row of each vehicle of process every time
The number carried in each evacuation website is moved, other data of output further include：The distance of each vehicle traveling, each vehicle driver are pre-
Count the working time, each object function result of calculation：Evacuate movable total deadline, when the average arrival of evacuation personnel
Between, all vehicles traveling total distance, in case decision-maker checks inspection.
Embodiment 2
This embodiment repeatedly dispatches emergency evacuation vehicle in specific road network, passes through analytical plan generating process
Timeliness and the stability of result of calculation verify the function of this system.
(1) data input
If sanctuary's number is 0, coordinate is (0,0), evacuates the coordinate of website and its waits for that number of evacuation is as shown in table 1.It is false
If vehicle is with freestream conditions in each sections of road, i.e., speed is stablized in free stream velocity, and each point is enabled to communicate with one another, into
And the most short running time between each website can be set as Euclidean distance value therebetween.If the emergency vehicles four that shared capacity is 5, are waited for
42 people of total number of persons is evacuated, then understands necessarily have vehicle action to be no less than 3 times.
1 point information table of table
Road net data, point interdigit travel time data, each website number, vehicle capacity and quantity needed for vehicle scheduling etc.
Data have been known, it is contemplated that do not make scheduling scheme excessively complicated, it is 3 that the maximum action number of each vehicle is enabled in this example.It will
In data entry system.
(2) vehicle scheduling schemes generation and output
Based on data above, emergency evacuation total deadline is enabled to be minimised as primary goal, passenger reaches the flat of sanctuary
The equal time is minimised as by-end, takes population scale 30, the iterations 200 of algorithm, carries out 10 checking computations, what is obtained is optimal
The desired value of scheme is respectively 67.2 points, 41.2 points, and (number is specific vehicle scheduling scheme after point bit number as shown in table 2
Carrying person numble of the vehicle in the website).
3 are shown in Table to the objectives value of 10 checking computations of the problem, it is known that algorithm is with good stability.This example calculates
It is intel i5 processors, meter that process, which uses MATLAB R2016a calculation by program, computer system win7, memory 2GB, CPU,
The mean time length of calculation about 90 seconds, has good computational efficiency.
When being scheduled scheme output, converts tertial vehicle route and Alternatives-carriers For Submarine in table 2 to word and issue
, by taking vehicle one as an example, stroke one：Parking lot is set out → website 8 (carrying 3 people) → website 9 (carrying 2 people) → return parking lot；
Stroke two：Parking lot is set out → website 5 (carrying 2 people) → website 6 (carrying 1 people) → website 7 (carrying 1 people) → return parking lot.
2 scheduling scheme table of table
3 target function value of table
Claims (1)
1. a kind of multiple batches of scheduling decision method of emergency evacuation vehicle, including data input module, data processing module and data
Output module, which is characterized in that method is as follows：
The data input module includes static and dynamic data input, storage and calling, and static data includes：Evacuation station
Point and parking lot geographical location, area road network, the road grid traffic flow of historical statistics, parking lot to each website shortest path, answer
Anxious vehicle fleet and capacity, static data need to be previously entered system and store, in case being carried out to it when vehicle route schemes generation
It calls；Wherein, the magnitude of traffic flow of the transit time in section based on section calculated using BPR functions, parking lot to each website most
Transit time of the short path based on road network and section is calculated using Dijkstra's algorithm；Dynamically data include：Each station
Point waits for that number of evacuation, the damage situation of road network, the real-time traffic flow data in each section, system can be according to the dynamic datas of input
Static data is updated and is supplemented, including the damage of certain section then updates the friendship of the connectivity data, section of road network in road network
Through-current capacity variation then updates its transit time according to BPR functions；
BPR function formulas are：
In formula：
T --- pass through the real time in section；
t0--- the free running time in section；
The volume of traffic in q --- section, unit pcu/h；
The actual capacity in C --- section, unit pcu/h；
α, β are model undetermined parameter, α=0.15, β=4；
The data processing module function is the scheme that the data based on data input module generate the multiple batches of scheduling of vehicle；It is first
First according to emergency evacuation the characteristics of, the target dispatch model of emergency evacuation vehicle is established, target dispatch model includes：It minimizes total
Deadline minimizes the average arrival time for waiting for evacuation personnel；
The minimum total deadline, i.e. target one are as follows：
In formula：
--- the time of v transport task before vehicle k is completed, k index for vehicle, and maximum value m, v index for the range of driving, maximum
Value is NMT；
Described minimizes the average arrival time for waiting for evacuation personnel, i.e. target two is as follows：
In formula：
--- decision variable, during vehicle k takes action at its v times, in the number that website i is carried, i indexes for site number, i=
0,1,2 ... n, 0 numbers for sanctuary；
R --- total number of persons to be evacuated；
Wherein, constraints is as follows：
In formula：
--- decision variable during vehicle k takes action at its v times, by arc (i, j), is to take 1, otherwise takes 0；
tij--- the running time between website i and j；
Q --- emergency vehicles maximum capacity；
si--- wait for number of evacuation at emergent website i；
The meaning of constraints is respectively：The calculating of vehicle travel time, each site traffic conservation, vehicle one way carrying person numble limit
System, all personnel are both needed to be evacuated, vehicle must could service it by way of certain website；
Secondly, it using quick non-dominated ranking algorithm, genetic algorithm, enhanced simulated annealing to mathematics model solution, adopts
Different scheduling schemes is ranked up according to the relative importance of object function with quick non-dominated ranking algorithm and grade
It divides, and by target one as the Main Basiss to solution sequence, target two is used as secondary foundation；Path is carried out by genetic algorithm
Generation, screening, the optimization of scheme, and in genetic algorithm iterative process, at interval of certain iterations, utilize improved mould
Quasi- annealing algorithm improves the local search ability of algorithm to current optimal solution re-optimization；Finally, according to the demand of policymaker or calculation
The end condition of method terminates to calculate, and obtains corresponding vehicle scheduling scheme；
Wherein, when carrying out the gene code of genetic algorithm, the length of coding is N × m × q,
N is the maximum times that each vehicle can take action, and m is the sum of vehicle, and q is bicycle capacity, and every disaster affected people is regarded
Make a basic gene point, and represented using the point serial number residing for it, then have in each encoding R website element and
N × m × q-R occupy-place element, R is total number of persons, represents the delivery of certain action of certain vehicle per continuous q element from the front to the back
And route plan, the sequence occurred according to site element in q element are determined to its access order, according to the number of site element
Amount determines that the handling capacity of passengers in the point, the genetic operators such as selection, variation, intersection use quick non-dominated sorted genetic algorithm；Together
When to improve local search efficiency, in an iterative process, call enhanced simulated annealing to carry out every certain algebraically
Local optimum is searched for, and enhanced simulated annealing formula is：
In formula：The new solution that P --- simulated annealing searches replaces the probability solved originally；
--- i-th of desired value of new explanation；
--- i-th of desired value of original solution；
α --- the constant between 0 to 1；
This called iterations of n --- simulated annealing；
The data outputting module function is that the numerical solution that data processing module generates is converted and exported, and exports content
Including：Number, each vehicle of each vehicle action take action every time process evacuation station number and sequence, each vehicle every time action exist
The number that each evacuation website is carried, other data of output further include：Distance, the estimated work of each vehicle driver of each vehicle traveling
Make the time, each object function result of calculation：Evacuate movable total deadline, the average arrival time that waits for evacuation personnel, institute
There is the total distance that vehicle travels, in case decision-maker checks inspection.
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| CN113762598A (en) * | 2021-08-05 | 2021-12-07 | 同济大学 | Comprehensive transportation junction emergency evacuation vehicle path planning method |
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