CN108492020A - Pollution vehicle dispatching method and system based on simulated annealing and branch's cutting optimization - Google Patents
Pollution vehicle dispatching method and system based on simulated annealing and branch's cutting optimization Download PDFInfo
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Abstract
The invention discloses a kind of pollution vehicle dispatching method and system based on simulated annealing and branch's cutting optimization, wherein method includes：Shipping model is established according to the dispatching parameter of acquisition, and carbon emission model is established according to load-carrying parameter and shipping model；Calculating is optimized to shipping model, carbon emission model and the preset capacity model of each vehicle using simulated annealing and branch's cutting algorithm, obtains every distribution route information；The optimization of pollution vehicle scheduling is finally completed according to distribution route information.The present invention first establishes relevant each model, recycles simulated annealing quickly to obtain integer solution, so as to get the operation time of integer solution is greatly reduced, and improves the efficiency of calculating；And construct simulated annealing for the generation of optimum integer solution in branch's cutting algorithm and to the improvement of optimal solution, improve the global optimizing ability of vehicle scheduling so that vehicle scheduling arrangement can reduce the discharge capacity of vehicle carbon dioxide to greatest extent.
Description
Technical field
The present invention relates to field of engineering technology, are related to a kind of pollution vehicle tune based on simulated annealing and branch's cutting optimization
Method and system is spent, for reducing motor vehicle exhaust emission in logistics distribution system and transportation system and reducing environmental pollution
Vehicle scheduling is planned.
Background technology
Climate change has become one of main threat in the whole world with greenhouse effects problem.Carbon dioxide, oxycarbide and sulphur
The toxic gases such as compound are one of the biggest factors for causing these to threaten.Current many companies are just being dedicated to reducing this from environment
The discharge of a little gases.In recent decades, the distribution via internet problem of low-carbon supply chain is always one of researcher's focus of attention.It is low
Carbon supply chain management receives the close attention of business and government in recent years.Supply chain is supplier, manufacturer, warehouse and dispatching
The network of center composition, so that customer obtains maximum benefit.Most important part is material in difference in supply chain system
Transport between the heart, such as supplier to manufacturer, manufacturer to warehouse and warehouse to dispatching node.
Vehicle dispatching problem (Vehicle Scheduling Problem, abbreviation VSP) is that traffic and transport field etc. is numerous
One of major issue in practical application.The discharge of carbon dioxide at present is one of the main problem of researcher's concern.Pollution
Vehicle dispatching problem (Pollution Vehicle Scheduling Problem, abbreviation PVSP) is the expansion of vehicle dispatching problem
Exhibition.The problem to environmental protection, reduce pernicious gas discharge play the role of it is vital.
In logistics transportation technology, discharge and its influence to environment that most enterprises ignore carbon dioxide.Recently,
Many companies and enterprise start to reduce the discharge capacity of carbon dioxide using different technologies.Distance is to reduce the master of carbon dioxide
Want one of factor, carbon dioxide proportional at a distance from running car.Vehicle dispatching problem is communications and transportation and supply chain management
One of main problem in system, vehicle dispatching problem are the integer programming problem in a Combinatorial Optimization.Its problem is, from
It send central warehouse to transport cargo and gives dispatching node, target is that total travel distance is made to minimize.In polluting vehicle dispatching problem, also
It will consider the minimum of CO2 emission.
Simulated annealing (Simulated Annealing Algorithm) is by Metropolis et al. in nineteen fifty-three
A kind of random optimizing algorithm proposed is a kind of algorithm based on probability imitating solid annealing theory, can be one big
Optimal solution is found in search space.Its process is from a certain higher initial temperature, with the continuous decline of temperature, in conjunction with it
The characteristic of probability kick can find the globally optimal solution of object function at random in solution space.Simulated annealing can be effective
Ground avoids being absorbed in local minimum and finally tends to global optimum, and local search ability is strong, and run time is shorter.Simulated annealing is calculated
Method has been applied to many field of engineering technology, including VLSI designs, Neuro-Net Computer, data mining and figure
As processing etc..But the ability of searching optimum of simulated annealing is poor, is easy to be influenced by parameter, it cannot be guaranteed that once converging to
Optimal value generally requires and repeatedly attempts to obtain.
Branch's cutting algorithm is a kind of algorithm that branch and bound method is combined with cutting plane algorithm.It can solve pure 0-1
Integer programming problem, and be applied to solve the problems, such as mixed 0-1 integer programming problem and mixed integer programming.The algorithm is very
It is generally applicable to the problem of the large-scale engineering problem with thousands of variables and other complexity.The algorithm synthesis point
Branch delimits method and the advantages of cutting plane algorithm, can effectively and rapidly find optimal solution, algorithm it is efficient.But branch's cutting is calculated
Method can not effectively solve all integer programming problems with extensive variable, which depends on sparse coefficient matrix, have
Certain limitation.
In conclusion currently, PVSP is a kind of current more complicated and scabrous vehicle dispatching problem, existing algorithm with
It dispatching node to be on the increase, calculation amount will be exponentially increased, and lead to calculate that effect is poor, time-consuming.Therefore, lack a kind of energy
The route of enough reasonable arrangement haulage vehicles, and improve the efficiency of transport truck goods delivery service, and reduce carbon emission into
One step reduces the pollution vehicle dispatching method and system based on simulated annealing and branch's cutting optimization of environmental pollution.
Invention content
The object of the present invention is to provide it is a kind of based on simulated annealing and branch cutting optimization pollution vehicle dispatching method and
System, is capable of the route of reasonable arrangement haulage vehicle, and improves the efficiency of transport truck goods delivery service, and reduces carbon emission
To be further reduced environmental pollution.
The pollution vehicle dispatching method optimized is cut based on simulated annealing and branch the present invention provides a kind of, including following
Step；
The dispatching parameter for obtaining each vehicle establishes shipping model according to the dispatching parameter；
The load-carrying parameter of each vehicle is obtained, and carbon emission model is established according to the load-carrying parameter and shipping model；
It is default to the shipping model, carbon emission model and each vehicle using simulated annealing and branch's cutting algorithm
Capacity model optimize calculating, obtain every distribution route information；
The optimization of pollution vehicle scheduling is completed according to the distribution route information.
As a kind of embodiment, it is described using simulated annealing and branch's cutting algorithm to the shipping model,
Carbon emission model and the preset capacity model of each vehicle optimize calculating, obtain every distribution route information, including following
Step；
The shipping model, carbon emission model and the preset capacity mould of each vehicle are constructed by frame of branch's cutting algorithm
The initial feasible solution of type, and the initial feasible solution is optimized with simulated annealing, obtain route initial solution；
Evaluation judgement is carried out to the target function value of each route initial solution according to preset initial enumeration tree, according to evaluation
As a result every distribution route information is obtained.
As a kind of embodiment, it is described according to preset initial enumeration tree to the object function of each route initial solution
Value carries out evaluation judgement, obtains distribution route information according to evaluation judging result, includes the following steps；
Whether the target function value for evaluating each route initial solution is optimal value, and the optimal objective function that evaluation is obtained
Value is added in the root node of the definition of preset Enumeration Tree；
Judge whether the Enumeration Tree meets end condition；
If the Enumeration Tree meets end condition, using each route initial solution as every distribution route information；
If the Enumeration Tree is unsatisfactory for end condition, the linear programming that each model is solved using branch's cutting algorithm is asked
It inscribes and constantly updates to obtain optimal solution, obtained from the score solution that the optimal solution is isolated using simulated annealing all whole
Number solution；And effective inequality is constructed to the integer solution, the inequality is detached using greedy constructivity is heuristic
To obtain new constraint；According to effective constraint re-optimization shipping model, returns each model and continues to update optimal solution,
Until not new solution is separated, creating node according to updated optimal solution is added in Enumeration Tree.
As a kind of embodiment, the dispatching parameter for obtaining each vehicle is established according to the dispatching parameter and is transported
Model includes the following steps；
The dispatching parameter of each vehicle is obtained, the dispatching parameter includes the enabling parameter m of each vehicleab, dispatching node ginseng
Number and distance parameter Lab, according to the enabling parameter mab, node parameter and distance parameter LabEstablish shipping model；
The shipping model is
Wherein, Minimize indicates minimum total dispatching distance；A indicates that a-th of dispatching node, b indicate b-th of dispatching section
Point, s indicate dispatching node total number；Distance parameter LabIndicate the distance from a-th of dispatching node to b-th of dispatching node；It enables
Parameter mabIt indicates to reinstate situation from a-th of dispatching node to the vehicle of b-th of dispatching node, works as mab=1 expression vehicle is reinstated,
mab=0 expression vehicle is not reinstated.
As a kind of embodiment, the load-carrying parameter for obtaining each vehicle, and according to the load-carrying parameter and transport
Model foundation carbon emission model, includes the following steps；
Obtain the load-carrying parameter of each vehicle, and the shipping model optimized into row distance, according to apart from optimum results and
The load-carrying parameter establishes carbon emission model；
The carbon emission model is CO2-Emission=H × Sv×Kf；
Wherein, CO2-EmissionIndicate minimum CO2 emissions；H indicates vehicle load；SvIndicate vehicle traveling
Average distance；KfIndicate that vehicle is averaged the CO2 emission coefficient of every kilometer of per unit load-carrying.
Correspondingly, the present invention also provides a kind of pollution vehicle dispatch system optimized based on simulated annealing and branch's cutting,
Including the first model building module, the second model building module, route optimization module and vehicle scheduling module；
First model building module, the dispatching parameter for obtaining each vehicle are established according to the dispatching parameter and are transported
Defeated model；
Second model building module, the load-carrying parameter for obtaining each vehicle, and according to the load-carrying parameter and fortune
Defeated model foundation carbon emission model；
The route optimization module, for utilizing simulated annealing and branch's cutting algorithm to the shipping model, carbon
Discharge model and the preset capacity model of each vehicle optimize calculating, obtain every distribution route information；
The vehicle scheduling module, the optimization for completing pollution vehicle scheduling according to the distribution route information.
As a kind of embodiment, the route optimization module includes structural unit and evaluation judging unit；
The structural unit, for using branch's cutting algorithm be the frame construction shipping model, carbon emission model and
The initial feasible solution of each preset capacity model of vehicle, and the initial feasible solution is optimized with simulated annealing, obtain road
Line initial solution；
The evaluation judging unit is used for according to preset initial enumeration tree to the target function value of each route initial solution
Evaluation judgement is carried out, every distribution route information is obtained according to evaluation result.
As a kind of embodiment, the evaluation judging unit includes evaluation subelement, judgment sub-unit, the first processing
Subelement and second processing subelement；
The evaluation subelement, whether the target function value for evaluating each route initial solution is optimal value, and will be commented
The optimal objective function value that valence obtains is added in the root node of the definition of preset Enumeration Tree；
The judgment sub-unit, for judging whether the Enumeration Tree meets end condition；
The first processing subelement makees each route initial solution if meeting end condition for the Enumeration Tree
For every distribution route information；
The second processing subelement utilizes branch's cutting algorithm if being unsatisfactory for end condition for the Enumeration Tree
The linear programming problem and continuous renewal for solving each model obtain optimal solution, are divided from the optimal solution using simulated annealing
All integer solutions are obtained in the score solution separated out；And effective inequality is constructed to the integer solution, it is opened using greedy constructivity
Hairdo detaches the inequality to obtain new constraint；According to effective constraint re-optimization shipping model, then return
Continue to update optimal solution to each model, until not new solution is separated, node is created according to updated optimal solution
It is added in Enumeration Tree.
As a kind of embodiment, first model building module includes that shipping model establishes unit；
The shipping model establishes unit, the dispatching parameter for obtaining each vehicle, and the dispatching parameter includes each vehicle
Enabling parameter mab, dispatching node parameter and distance parameter Lab, according to the enabling parameter mab, node parameter and away from
From parameter LabEstablish shipping model；
The shipping model is
Wherein, Minimize indicates minimum total dispatching distance；A indicates that a-th of dispatching node, b indicate b-th of dispatching section
Point, s indicate dispatching node total number；Distance parameter LabIndicate the distance from a-th of dispatching node to b-th of dispatching node；It enables
Parameter mabIt indicates to reinstate situation from a-th of dispatching node to the vehicle of b-th of dispatching node, works as mab=1 expression vehicle is reinstated,
mab=0 expression vehicle is not reinstated.
As a kind of embodiment, second model building module includes carbon emission model foundation unit；
The carbon emission model foundation unit, the load-carrying parameter for obtaining each vehicle, and the shipping model is carried out
Distance optimization, carbon emission model is established according to apart from optimum results and the load-carrying parameter；
The carbon emission model is CO2-Emission=H × Sv×Kf；
Wherein, CO2-EmissionIndicate minimum CO2 emissions；H indicates vehicle load；SvIndicate vehicle traveling
Average distance；KfIndicate that vehicle is averaged the CO2 emission coefficient of every kilometer of per unit load-carrying.
Compared with prior art, the technical program has the following advantages：
Pollution vehicle dispatching method and system provided by the invention based on simulated annealing and branch's cutting optimization, wherein
Method includes：Shipping model is established according to the dispatching parameter of acquisition, and carbon is established according to the load-carrying parameter and shipping model of acquisition
Discharge model；It is preset to shipping model, carbon emission model and each vehicle using simulated annealing and branch's cutting algorithm
Capacity model optimizes calculating, obtains every distribution route information；Pollution vehicle tune is finally completed according to distribution route information
The optimization of degree.The present invention first establishes relevant each model according to relevant parameter, and simulated annealing is recycled quickly to obtain
Take the integer solution of shipping model, carbon emission model and capacity model, so as to get the operation time of integer solution is greatly reduced, and carries
The high efficiency calculated；And it constructs simulated annealing for the generation of optimum integer solution in branch's cutting algorithm and to most
The improvement of excellent solution improves the global optimizing ability of vehicle scheduling, shortens the time of route planning between dispatching node so that
The every distribution route information obtained after branch's cutting completes the optimization of pollution vehicle scheduling so that vehicle scheduling arrangement can be most
The discharge capacity of the reduction vehicle carbon dioxide of limits, and logistics transportation cost is greatly lowered, it has important practical significance.
Description of the drawings
Fig. 1 is the pollution vehicle dispatching method based on simulated annealing and branch's cutting optimization that the embodiment of the present invention one provides
Flow diagram；
Fig. 2 is the flow diagram of the Optimization Steps cut with branch using simulated annealing in the embodiment of the present invention one；
Fig. 3 a are the schematic diagram before union operation in the embodiment of the present invention one；
Fig. 3 b are the schematic diagram after union operation in the embodiment of the present invention one；
Fig. 4 a are the schematic diagram before swap operation in the embodiment of the present invention one；
Fig. 4 b are the schematic diagram after swap operation in the embodiment of the present invention one；
Fig. 5 a are the schematic diagram before gas station's insertion operation in the embodiment of the present invention one；
Fig. 5 b are the schematic diagram after gas station's insertion operation in the embodiment of the present invention one；
Fig. 6 a are the schematic diagram before gas station's lock out operation in the embodiment of the present invention one；
Fig. 6 b are the schematic diagram after gas station's lock out operation in the embodiment of the present invention one；
Fig. 7 is the pollution vehicle dispatch system provided by Embodiment 2 of the present invention based on simulated annealing and branch's cutting optimization
Structural schematic diagram；
Fig. 8 is the structural schematic diagram of route optimization module in Fig. 7；
Fig. 9 is the structural schematic diagram that judging unit is evaluated in Fig. 8.
In figure：100, the first model building module；110, shipping model establishes unit；200, the second model building module；
210, carbon emission model foundation unit；300, route optimization module；310, structural unit；320, judging unit is evaluated；321, it comments
Valence subelement；322, judgment sub-unit；323, the first processing subelement；324, second processing subelement；400, vehicle scheduling mould
Block.
Specific implementation mode
Below in conjunction with attached drawing, the technical characteristic and advantage above-mentioned and other to the present invention are clearly and completely described,
Obviously, described embodiment is only the section Example of the present invention, rather than whole embodiments.
It is one of vehicle dispatching problem of standard to pollute vehicle dispatching problem.There are two targets for this problem：First mesh
Mark is to find minimum operating range, and second target is the minimum emissions for finding carbon dioxide.PVSP schemes determine one group of fortune
Route is sent, disclosure satisfy that the requirement of home-delivery center, while being obtained from home-delivery center to transport trip minimum each dispatching node
Cost.In general, total least cost is equivalent to the total distance of all vehicle travelings.Assuming that there are enough vehicle numbers in enterprise, often
A dispatching node only allows to be dispensed using a vehicle.All vehicles all have maximum capacity limitation, they by cargo from
It send center to be transported to dispatching node, then returnes to home-delivery center.
To achieve the above object, the present invention uses following technical scheme：First, a kind of vehicle based on distance and load-carrying is introduced
Carbon emission model, that is, the discharge capacity of vehicle is proportional to its operating range and loading capacity.And relevant shipping model and capacity
Model.Then, propose that a kind of hybrid intelligent method cut based on simulated annealing and branch calculates minimum operating range and minimum
Carbon emission amount.It is as follows.
Referring to Fig. 1, the pollution vehicle tune based on simulated annealing and branch's cutting optimization that the embodiment of the present invention one provides
Degree method, includes the following steps；
S100, the dispatching parameter for obtaining each vehicle establish shipping model according to dispatching parameter；
S200, the load-carrying parameter for obtaining each vehicle, and carbon emission model is established according to load-carrying parameter and shipping model；
It is S300, pre- to shipping model, carbon emission model and each vehicle using simulated annealing and branch's cutting algorithm
If capacity model optimize calculating, obtain every distribution route information；
S400, the optimization that pollution vehicle scheduling is completed according to distribution route information.
It should be noted that establishing the relevant parameter of model can directly obtain from local data base, can also utilize
Big data is obtained from Cloud Server.Here relevant parameter refers to dispatching parameter, load-carrying parameter and preset capacity mould
Type.It includes being not limited to the enabling parameter m of each vehicle to dispense parameterab, dispatching node parameter and distance parameter Lab, according to opening
With parameter mab, node parameter and distance parameter LabEstablish shipping model；Assuming that there are enough vehicle numbers in enterprise, it is each to dispense
Node only allows to be dispensed using a vehicle, calculates the total travel distance of vehicle, i.e., all the sum of total distances for reinstating vehicle.
Shipping model is the minimum value for calculating total distance.In other embodiment, it is also contemplated that the vehicle number that enterprise is not enough,
In this present embodiment, it is not limited.
The shipping model so established is
Wherein, Minimize indicates minimum total dispatching distance；A indicates that a-th of dispatching node, b indicate b-th of dispatching section
Point, s indicate dispatching node total number；Distance parameter LabIndicate the distance from a-th of dispatching node to b-th of dispatching node；It enables
Parameter xijIt indicates to reinstate situation from a-th of dispatching node to the vehicle of b-th of dispatching node, works as mab=1 expression vehicle is reinstated,
mab=0 expression vehicle is not reinstated.
Each preset capacity model of vehicle is a constraints, that is, require its it is all dispatching nodes by vehicle capacity
No more than C, capacity model is
Wherein, caIndicate the demand of a-th of dispatching node, nakIndicate that node is dispensed at a-th has used k-th vehicle
Situation.Q indicates maximum vehicle number amount, i.e. when k=1, indicates the 1st vehicle, when k=q, indicates q-th of vehicle.C expressions pass through
The maximum capacity of vehicle.nak=1 indicates that node is dispensed at a-th has used kth vehicle, nak=0 indicates to dispense section at a-th
Point is without using kth vehicle.
In this present embodiment, carbon emission model is to establish load-carrying parameter and shipping model as the relevant parameter of foundation
, specific steps may include：The load-carrying parameter of each vehicle is obtained, and shipping model is optimized into row distance, according to apart from excellent
Change result and load-carrying parameter establishes carbon emission model；Carbon emission model is CO2-Emission=H × Sv×Kf；
Wherein, CO2-EmissionIndicate minimum CO2 emissions；H indicates vehicle load；SvIndicate vehicle traveling
Average distance；KfIndicate that vehicle is averaged the CO2 emission coefficient of every kilometer of per unit load-carrying.In other embodiment, carbon row
Putting model can be established with direct basis relevant parameter, without the data being first associated in carbon emission model.But this kind of scheme
Still it is relevant to need to calculate transportation range and vehicle in the average distance and shipping model that vehicle travels in carbon emission model again
Data relationship so that operation efficiency reduces, and increases complexity.
In order to avoid being on the increase with dispatching node in traditional algorithm, calculation amount will be exponentially increased, and cause to calculate
The problem of effect is poor, time-consuming.Using simulated annealing and branch's cutting algorithm to shipping model, carbon emission model and each
The preset capacity model of vehicle optimizes calculating, obtains every distribution route information.Come faster first with simulated annealing
Ground obtains the integer solution of shipping model, carbon emission model and capacity model, reconstructs and cuts simulated annealing for branch
The generation of optimum integer solution and the improvement to optimal solution in algorithm are cut, to reach the purpose that rapid Optimum pollutes vehicle scheduling.
And every distribution route information includes at least one section of distribution route.Here each distribution route is referred to home-delivery center extremely
Node (dispatching node), dispatching node to dispatching node and dispatching node are dispensed to route informations such as home-delivery centers.By each
Vehicle is dispatched according to corresponding every distribution route format, you can completes the optimization of pollution vehicle scheduling.Meanwhile in the present invention
The technical solution stated can also be applied in the technical fields such as Features of Railway Logistics scheduling, robot scheduling and artificial intelligence.
Pollution vehicle dispatching method and system provided by the invention based on simulated annealing and branch's cutting optimization, wherein
Method includes：Shipping model is established according to the dispatching parameter of acquisition, and carbon is established according to the load-carrying parameter and shipping model of acquisition
Discharge model；It is preset to shipping model, carbon emission model and each vehicle using simulated annealing and branch's cutting algorithm
Capacity model optimizes calculating, obtains every distribution route information；Pollution vehicle tune is finally completed according to distribution route information
The optimization of degree.The present invention first establishes relevant each model according to relevant parameter, and simulated annealing is recycled quickly to obtain
Take the integer solution of shipping model, carbon emission model and capacity model, so as to get the operation time of integer solution is greatly reduced, and carries
The high efficiency calculated；And it constructs simulated annealing for the generation of optimum integer solution in branch's cutting algorithm and to most
The improvement of excellent solution improves the global optimizing ability of vehicle scheduling, shortens the time of route planning between dispatching node so that
The every distribution route information obtained after branch's cutting completes the optimization of pollution vehicle scheduling so that vehicle scheduling arrangement can be most
The discharge capacity of the reduction vehicle carbon dioxide of limits, and logistics transportation cost is greatly lowered, it has important practical significance.
Further, step S300 includes the following steps；
S310, shipping model, carbon emission model and the preset capacity of each vehicle are constructed by frame of branch's cutting algorithm
The initial feasible solution of model, and initial feasible solution is optimized with simulated annealing, obtain route initial solution；
S320, evaluation judgement, root are carried out to the target function value of each route initial solution according to preset initial enumeration tree
Every distribution route information is obtained according to evaluation result.
Shipping model, carbon emission model and the preset capacity model of each vehicle are being constructed by frame of branch's cutting algorithm
Route initial feasible solution when, first, a simple route is established from home-delivery center for each dispatching node.Then, it is solving
Certainly all route (T in scheme1,T2) in, check the saving cost obtained when they merge, and provide most by merging
Big a pair of of the dispatching node for saving cost merges to realize.The route saved with maximum merges a pair of of dispatching node at original,
I.e. initial feasible solution is also by merging optimization.Certainly in certain special cases, it is possible that being unsatisfactory for merging condition
Solution, start to calculate then can redistribute and establish simple route, that is to say, that initial feasible solution is the data acquisition system of route.
Initial feasible solution is optimized with simulated annealing again, the process of optimization is to use random search techniques, is specially used
The modes such as the mode of neighborhood search is merged, exchanged, gas station is inserted into and gas station detaches.It is initial to make to obtain route
Solution is to be greatly reduced the operation time of integer solution, improves the efficiency of calculating.
Preset initial enumeration tree carries out evaluation to the target function value of each route initial solution and judges it is a cycle
Process, it can be understood as only after meeting end condition, can just obtain every final distribution route information.Here termination
Condition refers to whether Enumeration Tree is empty set, i.e. Enumeration TreeOr other end conditions.For example, other end conditions are fortune
Calculate mistake, Infinite Cyclic etc..To ensure the efficiency calculated.
Further, step S320 includes the following steps；
Whether S321, the target function value for evaluating each route initial solution are optimal value, and the optimal mesh that evaluation is obtained
Offer of tender numerical value is added in the root node of the definition of preset Enumeration Tree；
S322, whether meet end condition to Enumeration Tree and judge；
If S323, Enumeration Tree meet end condition, using each route initial solution as every distribution route information；
If S324, Enumeration Tree are unsatisfactory for end condition, the linear programming of each model is solved using branch's cutting algorithm
Problem and constantly update obtain optimal solution, obtain all integers in the score solution isolated from optimal solution using simulated annealing
Solution；And effective inequality is constructed to integer solution, inequality is subjected to separation to obtain newly using greedy constructivity is heuristic
Constraint；According to effective constraint re-optimization shipping model, returns each model and continue to update optimal solution, until not new
Solution be separated, according to updated optimal solution create node be added in Enumeration Tree.
Whether the process of evaluation is actually that optimal value evaluated to the target function value of each route initial solution
Journey.Specifically it is to be understood that if there is optimal value, then it will evaluate obtained optimal objective function value and be added to preset enumerate
In the root node of the definition of tree, that is, end condition is not met, will continue to update and obtain new route initial solution.Meanwhile it deleting
Corresponding node in Enumeration Tree.If route initial solution cannot get optimal value after evaluation, meet end condition, by each road
Line initial solution is as every distribution route information.
And the present invention constructs effective inequality to integer solution, is obtained using the heuristic separation inequality of greedy constructivity
Effective constraint enables the integer for the high quality that branch's cutting algorithm updates after being detached, significantly reduces branch's cutting
Algorithm detaches the potential score solution comprising optimal integer solution and is affected, and improves the efficiency of algorithm.
As shown in Fig. 2, the above-mentioned Optimization Steps cut with branch using simulated annealing are described in detail in citing below,
Specifically it may comprise steps of.
Step 2.1, initial feasible solution is constructed.
First, it is that each dispatching node establishes a simple route from home-delivery center.Then, institute in a solution
Some route (T1,T2) in, check the saving cost obtained when they merge, and maximum saving cost is provided by merging
A pair of of node merges to realize.Cost is saved for combined condition, to construct initial feasible solution with maximum.
Step 2.2, the combination for determining whether the condition of satisfaction, return to step 2.1 re-executes if having, if not having, after
Continuous next step.
Step 2.3, the initial solution of branch's cutting algorithm is obtained.
In initial feasible solution R '0After generation, the initial solution R of branch's cutting algorithm is obtained by simulated annealing0.Mould
Quasi- annealing algorithm is a kind of random search techniques, and carrying out neighborhood search operator using simulated annealing has merging, exchange, oiling
Stand insertion and gas station separation processing.
Union operation is as shown in Figure 3a and Figure 3b shows, random selection two lines (T1,T2), T2(0-4-2-0) passes through T1 (0-
Each optimum position 6-3-5-1-0), and best feasible location is selected, by route T1(0-6-3-5-1-0) and T2(0-4-2-0)
It is merged into a new route (0-6-3-5-4-2-1-0).Swap operation is selected at random as shown in figures 4 a and 4b, by two
Dispatching node swapped in same route or in two different routes, i.e., will dispatching node 1 and 8 exchanged, exchange
Route afterwards is (0-5-3-7-4-8-0) and (0-1-6-2-0) referring to Fig. 4 b.Gas station's insertion operation such as Fig. 5 a and Fig. 5 b institutes
Show, continuously select two random dispatching nodes, if between them not by gas station if gas station is added on route.
Gas station 3 is nearest apart from dispatching node 6 and dispatching node 2, then inserts gas station between dispatching node 6 and dispatching node 2
3.The merging route (0-1-6-3-2-0) and (0-5-7-4-0) that is iterating through next time becomes a new road after the insertion
Line (0-1-6-3-2-5-7-4-0).Gas station's lock out operation as shown in figures 6 a and 6b, deletes one at random if feasible
The gas station of selection, the gas station 3 for dispensing node 2 and dispensing between node 9 are deleted, and are added to one for these dispatching nodes
The new route of item.
Step 2.4, initial enumeration tree is constructed.
In order to construct an initial Enumeration Tree, firstly, it is necessary to obtain all initial solutions, the mesh of each initial solution is evaluated
Offer of tender numerical value f (S0), the definition method of optimal value and optimal objective value is as follows：Rb←R0,f(Rb)←f(R0)。
Wherein, RbThe optimal value in current all initial solutions, f (R are indicated in formulab) indicate the target letter of the optimal value
Numerical value.The node for defining an Enumeration Tree, f (R are assigned to by valueb), and be added in the root node of Enumeration Tree Θ using as working as
Front nodal point d.
Step 2.5, determine whether Enumeration TreeOr end condition meets, and if it exists, then returns to Rb, algorithm stopping；Instead
It, comes out from Enumeration Tree by a node d.
Step 2.6, linear programming problem is solved, update obtains new optimal solution.
Corresponding linear programming problem is solved, to obtain optimal solutionThis optimal solution is likely to be score.JudgeIt is
It is no to meet condition, current node is deleted from Enumeration Tree if being unsatisfactory for, gos to step 2.5；It judges whetherIf then deleting current node from Enumeration Tree, 2.5 are gone to step；JudgeWhether it is integer, if
It is to judge whether againIf so then execute following operation：
Above-mentioned formula indicates update optimal solution, continues to execute in next step；Conversely, current node is deleted from Enumeration Tree,
Go to step 2.5.If not being above, continue to execute in next step.
Step 2.7, the integer solution of high quality is obtained from score solution.
It observes that optimal score solution may include some information about optimal integer solution, then inspires likely via using
Formula or accurate solution preocess obtain the integer solution of high quality.IfWithIt is the optimal solution of any node in Enumeration Tree.First,
Route T is by selection with maximum(or) dispatching node a*Start, is then persistently added in route T
One new dispatching node b*With maximum(or) to the route of last one dispatching node, on condition that addition is can
Capable, above step is repeated, until all dispatching nodes have all been assigned to route.Generate a feasible solution R 'tAfterwards, Ke Yitong
It crosses step 2.4 and obtains an improved solutionIn order to reduce the calculating time that this process is spent, by simulated annealing application
All nodes in all nodes and Enumeration Tree within to ten grades of depth in the every ten depth rank.
Step 2.8, effective inequality is determined.
In branch's cutting algorithm of the present invention, because only that a constraint, so starting in algorithm there are one inequality
When be directly applied in algorithm model, which is defined as follows：
Wherein, UK={ u1,u2,...,ukIndicate dispatching node.SF={ uK+1,uK+2,...,uK+SIndicate to refuel
It stands.S(UK) indicate minimum vehicle number.mabIndicate binary variable, if vehicle directly from node a to node b if be equal to 1, it is no
It is then 0.nabkIndicate binary variable, if vehicle by fuel station F from node a to node b if be equal to 1, be otherwise 0.
Then, the process of constraint is obtained there are one needing.For this purpose, introducing a heuristic process of greedy constructivity to divide
From these inequality.In the iteration each time of this process, a dispatching node is randomly choosed as seed node, dispatching section
This seed initialization of point set X.Then, a new dispatching node x is selected*, X is to pass through x*It is extended, i.e. X ←
XYx*.The definition difference of relaxation value is as follows：
Wherein, x indicates that the quantity of vehicle can be used.HmaxIndicate a workaday duration.Value and value ' points
It Biao Shi not two relaxation values.Indicate total road without sequence information using the first and second nearest nodes in XYx ranges
The time valuation of line.U indicates set i.e. U=" 0 " YU of all nodesKYSF, " 0 " indicates home-delivery center.It indicates to save from a
Point sets out only returns the time of home-delivery center by b nodes.It indicates from home-delivery center only by b nodes again to a
The time of node.Indicate from node a it is intermediate successively only by gas station's f and b node return home-delivery center when
Between.Indicate intermediate successively only by gas station's f and b node again to the time of a nodes from home-delivery center.It obtains minimum
The process for changing constraint relaxation is as follows：
Wherein, argmin { valuexAnd argmin { value ＇xIndicate to instigate to obtain relaxation value function value respectivelyxWith
Value ＇xObtain the set of all independent variable x of its minimum value.
Step 2.9, constraint validity is checked.
As selection dispatching node x*When, check the validity of present confinement.The case where in case of set X is violated, then
It is added in cutup pool.This process is repeated, until finding all notch to violate the rules.These notch are applied
To LP models and re-optimization.
Step 2.10, new node is created.
A non-integer decision variable is selected according to branching rule, create a new node and is added to Enumeration Tree
Θ goes to step 2.5.
To improve the optimization efficiency of pollution vehicle scheduling so that vehicle scheduling arrangement can reduce vehicle to greatest extent
The discharge capacity of carbon dioxide, and logistics transportation cost is greatly lowered.
Based on same inventive concept, the embodiment of the present invention also provides a kind of dirt based on simulated annealing and branch's cutting optimization
Vehicle dispatch system is contaminated, the implementation of the system can refer to the process realization of the above method, it is no longer redundant later to repeat place.
As shown in fig. 7, being the pollution vehicle provided by Embodiment 2 of the present invention based on simulated annealing and branch's cutting optimization
The structural schematic diagram of scheduling system, including the first model building module 100, the second model building module 200, route optimization module
300 and vehicle scheduling module 400；First model building module 100 is used to obtain the dispatching parameter of each vehicle, is joined according to dispatching
Number establishes shipping model；Second model building module 200 is used to obtain the load-carrying parameter of each vehicle, and according to load-carrying parameter and fortune
Defeated model foundation carbon emission model；Route optimization module 300 is used for using simulated annealing and branch's cutting algorithm to transport
Model, carbon emission model and the preset capacity model of each vehicle optimize calculating, obtain every distribution route information；Vehicle
Scheduler module 400 is used to complete the optimization of pollution vehicle scheduling according to distribution route information.
The present invention first establishes relevant each model according to relevant parameter, and simulated annealing is recycled quickly to obtain
The integer solution of shipping model, carbon emission model and capacity model, so as to get the operation time of integer solution is greatly reduced, and improves
The efficiency calculated；And it constructs simulated annealing for the generation of optimum integer solution in branch's cutting algorithm and to optimal
The improvement of solution improves the global optimizing ability of vehicle scheduling, shortens the time of route planning between dispatching node so that point
The every distribution route information obtained after branch cutting completes the optimization of pollution vehicle scheduling so that vehicle scheduling arrangement can be maximum
The discharge capacity of the reduction vehicle carbon dioxide of limit, and logistics transportation cost is greatly lowered, it has important practical significance.
As shown in figure 8, for the structural schematic diagram of route optimization module 300, including structural unit 310 and evaluation judging unit
320；Structural unit 310 is used to construct shipping model, carbon emission model and each vehicle using branch's cutting algorithm as frame default
Capacity model initial feasible solution, and initial feasible solution is optimized with simulated annealing, obtains route initial solution；Evaluation is sentenced
Disconnected unit 320 is used to carry out evaluation judgement, root to the target function value of each route initial solution according to preset initial enumeration tree
Every distribution route information is obtained according to evaluation result.
As shown in figure 9, for the structural schematic diagram of evaluation judging unit 320, including evaluation subelement 321, judgment sub-unit
322, the first processing subelement 323 and second processing subelement 324；Evaluation subelement 321 is initial for evaluating each route
Whether the target function value of solution is optimal value, and the optimal objective function value that evaluation obtains is added to determining for preset Enumeration Tree
In the root node of justice；Judgment sub-unit 322 is for judging whether Enumeration Tree meets end condition；First processing subelement
If 323 meet end condition for Enumeration Tree, using each route initial solution as every distribution route information；Second processing
If unit 324 is unsatisfactory for end condition for Enumeration Tree, the linear programming that each model is solved using branch's cutting algorithm is asked
It inscribes and constantly updates to obtain optimal solution, all integers are obtained in the score solution isolated from optimal solution using simulated annealing
Solution；And effective inequality is constructed to integer solution, inequality is subjected to separation to obtain newly using greedy constructivity is heuristic
Constraint；According to effective constraint re-optimization shipping model, returns each model and continue to update optimal solution, until not new
Solution be separated, according to updated optimal solution create node be added in Enumeration Tree.
Further, for simplified model parameter, the first model building module 100 establishes unit 110 including shipping model；
Shipping model establishes unit 110, the dispatching parameter for obtaining each vehicle, and dispatching parameter includes the enabling parameter m of each vehicleab、
The node parameter and distance parameter L of dispatchingab, according to enabling parameter mab, node parameter and distance parameter LabEstablish transport mould
Type；
Shipping model is
Wherein, Minimize indicates minimum total dispatching distance；A indicates that a-th of dispatching node, b indicate b-th of dispatching section
Point, s indicate dispatching node total number；Distance parameter LabIndicate the distance from a-th of dispatching node to b-th of dispatching node；It enables
Parameter mabIt indicates to reinstate situation from a-th of dispatching node to the vehicle of b-th of dispatching node, works as mab=1 expression vehicle is reinstated,
mab=0 expression vehicle is not reinstated.
Further, in order to enhance two model interactions, operand is reduced, the second model building module 200 is arranged including carbon
Put model foundation unit 210；Carbon emission model foundation unit 210, the load-carrying parameter for obtaining each vehicle, and to shipping model
Optimize into row distance, carbon emission model is established according to apart from optimum results and load-carrying parameter；
Carbon emission model is CO2-Emission=H × Sv×Kf；
Wherein, CO2-EmissionIndicate minimum CO2 emissions；H indicates vehicle load；SvIndicate vehicle traveling
Average distance；KfIndicate that vehicle is averaged the CO2 emission coefficient of every kilometer of per unit load-carrying.
Although the invention has been described by way of example and in terms of the preferred embodiments, but it is not for limiting the present invention, any this field
Technical staff without departing from the spirit and scope of the present invention, may be by the methods and technical content of the disclosure above to this hair
Bright technical solution makes possible variation and modification, therefore, every content without departing from technical solution of the present invention, and according to the present invention
Technical spirit to any simple modifications, equivalents, and modifications made by above example, belong to technical solution of the present invention
Protection domain.
Claims (10)
1. a kind of pollution vehicle dispatching method based on simulated annealing and branch's cutting optimization, which is characterized in that including following step
Suddenly；
The dispatching parameter for obtaining each vehicle establishes shipping model according to the dispatching parameter；
The load-carrying parameter of each vehicle is obtained, and carbon emission model is established according to the load-carrying parameter and shipping model；
Using simulated annealing and branch's cutting algorithm to the shipping model, carbon emission model and the preset appearance of each vehicle
Amount model optimizes calculating, obtains every distribution route information；
The optimization of pollution vehicle scheduling is completed according to the distribution route information.
2. the pollution vehicle dispatching method based on simulated annealing and branch's cutting optimization, feature exist as described in claim 1
In described default to the shipping model, carbon emission model and each vehicle using simulated annealing and branch's cutting algorithm
Capacity model optimize calculating, obtain every distribution route information, include the following steps；
The shipping model, carbon emission model and the preset capacity model of each vehicle are constructed by frame of branch's cutting algorithm
Initial feasible solution, and the initial feasible solution is optimized with simulated annealing, obtain route initial solution；
Evaluation judgement is carried out to the target function value of each route initial solution according to preset initial enumeration tree, according to evaluation result
Obtain every distribution route information.
3. the pollution vehicle dispatching method based on simulated annealing and branch's cutting optimization, feature exist as claimed in claim 2
In, it is described that evaluation judgement is carried out to the target function value of each route initial solution according to preset initial enumeration tree, according to evaluation
Judging result obtains distribution route information, includes the following steps；
Whether the target function value for evaluating each route initial solution is optimal value, and the optimal objective function value that evaluation obtains is added
It is added in the root node of the definition of preset Enumeration Tree；
Judge whether the Enumeration Tree meets end condition；
If the Enumeration Tree meets end condition, using each route initial solution as every distribution route information；
If the Enumeration Tree is unsatisfactory for end condition, the linear programming problem of each model is solved simultaneously using branch's cutting algorithm
Continuous renewal obtains optimal solution, and all integers are obtained from the score solution that the optimal solution is isolated using simulated annealing
Solution；And effective inequality is constructed to the integer solution, using greedy constructivity it is heuristic by the inequality detach from
And obtain new constraint；According to effective constraint re-optimization shipping model, returns each model and continue to update optimal solution, directly
It is separated to not new solution, creating node according to updated optimal solution is added in Enumeration Tree.
4. the pollution vehicle dispatching method based on simulated annealing and branch's cutting optimization, feature exist as described in claim 1
In the dispatching parameter for obtaining each vehicle is established shipping model according to the dispatching parameter, included the following steps；
The dispatching parameter of each vehicle is obtained, the dispatching parameter includes the enabling parameter m of each vehicleab, dispatching node parameter with
And distance parameter Lab, according to the enabling parameter mab, node parameter and distance parameter LabEstablish shipping model；
The shipping model is
Wherein, Minimize indicates minimum total dispatching distance；A indicates that a-th of dispatching node, b indicate b-th of dispatching node, s
Indicate dispatching node total number；Distance parameter LabIndicate the distance from a-th of dispatching node to b-th of dispatching node；Enable parameter
mabIt indicates to reinstate situation from a-th of dispatching node to the vehicle of b-th of dispatching node, works as mab=1 expression vehicle is reinstated, mab=0
Indicate that vehicle is not reinstated.
5. the pollution vehicle dispatching method based on simulated annealing and branch's cutting optimization, feature exist as described in claim 1
Carbon emission model is established in, the load-carrying parameter for obtaining each vehicle, and according to the load-carrying parameter and shipping model, including with
Lower step；
It obtains the load-carrying parameter of each vehicle, and the shipping model is optimized into row distance, according to apart from optimum results and described
Load-carrying parameter establishes carbon emission model；
The carbon emission model is CO2-Emission=H × Sv×Kf；
Wherein, CO2-EmissionIndicate minimum CO2 emissions；H indicates vehicle load；SvIndicate being averaged for vehicle traveling
Distance；KfIndicate that vehicle is averaged the CO2 emission coefficient of every kilometer of per unit load-carrying.
6. a kind of pollution vehicle dispatch system based on simulated annealing and branch's cutting optimization, which is characterized in that including the first mould
Type establishes module, the second model building module, route optimization module and vehicle scheduling module；
First model building module, the dispatching parameter for obtaining each vehicle establish transport mould according to the dispatching parameter
Type；
Second model building module, the load-carrying parameter for obtaining each vehicle, and according to the load-carrying parameter and transport mould
Type establishes carbon emission model；
The route optimization module, for utilizing simulated annealing and branch's cutting algorithm to the shipping model, carbon emission
Model and the preset capacity model of each vehicle optimize calculating, obtain every distribution route information；
The vehicle scheduling module, the optimization for completing pollution vehicle scheduling according to the distribution route information.
7. the pollution vehicle dispatch system based on simulated annealing and branch's cutting optimization, feature exist as claimed in claim 6
In the route optimization module includes structural unit and evaluation judging unit；
The structural unit, for constructing the shipping model, carbon emission model and each vehicle by frame of branch's cutting algorithm
The initial feasible solution of preset capacity model, and the initial feasible solution is optimized with simulated annealing, at the beginning of obtaining route
Begin solution；
The evaluation judging unit, for being carried out to the target function value of each route initial solution according to preset initial enumeration tree
Evaluation judges, every distribution route information is obtained according to evaluation result.
8. the pollution vehicle dispatch system based on simulated annealing and branch's cutting optimization, feature exist as claimed in claim 7
In the evaluation judging unit includes that evaluation subelement, judgment sub-unit, the first processing subelement and second processing are single
Member；
The evaluation subelement, whether the target function value for evaluating each route initial solution is optimal value, and will be evaluated
To the optimal objective function value definition that is added to preset Enumeration Tree root node in；
The judgment sub-unit, for judging whether the Enumeration Tree meets end condition；
The first processing subelement, if meeting end condition for the Enumeration Tree, using each route initial solution as every
Distribution route information；
The second processing subelement is solved if being unsatisfactory for end condition for the Enumeration Tree using branch's cutting algorithm
The linear programming problem of each model and continuous renewal obtains optimal solution, is isolated using simulated annealing from the optimal solution
Score solution in obtain all integer solutions；And effective inequality is constructed to the integer solution, it is heuristic using greedy constructivity
The inequality is detached to obtain new constraint；According to effective constraint re-optimization shipping model, return each
A model continues to update optimal solution, and until not new solution is separated, creating node according to updated optimal solution adds
Into Enumeration Tree.
9. the pollution vehicle dispatch system based on simulated annealing and branch's cutting optimization, feature exist as claimed in claim 6
In first model building module includes that shipping model establishes unit；
The shipping model establishes unit, the dispatching parameter for obtaining each vehicle, and the dispatching parameter includes opening for each vehicle
With parameter mab, dispatching node parameter and distance parameter Lab, according to the enabling parameter mab, node parameter and apart from ginseng
Number LabEstablish shipping model；
The shipping model is
Wherein, Minimize indicates minimum total dispatching distance；A indicates that a-th of dispatching node, b indicate b-th of dispatching node, s
Indicate dispatching node total number；Distance parameter LabIndicate the distance from a-th of dispatching node to b-th of dispatching node；Enable parameter
mabIt indicates to reinstate situation from a-th of dispatching node to the vehicle of b-th of dispatching node, works as mab=1 expression vehicle is reinstated, mab=0
Indicate that vehicle is not reinstated.
10. the pollution vehicle dispatch system based on simulated annealing and branch's cutting optimization, feature exist as claimed in claim 6
In second model building module includes carbon emission model foundation unit；
The carbon emission model foundation unit, the load-carrying parameter for obtaining each vehicle, and to the shipping model into row distance
Optimization, carbon emission model is established according to apart from optimum results and the load-carrying parameter；
The carbon emission model is CO2-Emission=H × Sv×Kf；
Wherein, CO2-EmissionIndicate minimum CO2 emissions；H indicates vehicle load；SvIndicate being averaged for vehicle traveling
Distance；KfIndicate that vehicle is averaged the CO2 emission coefficient of every kilometer of per unit load-carrying.
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