CN104036333A - Algorithm for solving single-depot time-varying associated logistics transportation vehicle routing problem - Google Patents
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Abstract
The invention discloses an algorithm for solving a single-depot time-varying associated logistics transportation vehicle routing problem. The algorithm includes that a chaos taboo search algorithm is adopted, the algorithm takes speed time-varying influence in the process of vehicle traveling into consideration, an association form is added into a target function in a manner of associating penalty cost, and a math model of the single-depot time-varying associated logistics transportation vehicle routing problem is built; on the basis of the math model, the chaos taboo search algorithm is provided to solve the problem. A taboo search algorithm is improved by utilizing advantages, of a chaos search mechanism, like globality, randomness and ergodicity. A 2-opt mode and a routing point two-point exchange mode are used in the process of neighborhood structuring. Finish criteria of specified iteration steps and optimal solution maximum unchanged times are used to finish the algorithm, so that solving quality and convergence speed of the algorithm are improved to some extent.
Description
Technical field
The invention belongs to field of engineering technology, the chaos tabu search that becomes associated transport truck routing problem while relating to a kind of bicycle field is calculated.
Background technology
Dispensing is the core link of logistics system, is to be accompanied by market and a kind of inevitable market behavior of being born, and along with the fierceness day by day of market competition and improving constantly of customer requirement, dispensing will be played very important effect in following market competition.In dispensing business, the involvement aspect of Optimized scheduling of distribution vehicles problem is wider, needs the factor of consideration also a lot, and the impact of distribution enterprise being improved service quality, reduced operating cost, increase economic benefit is also very large.Chinese scholars is put forth effort on research Vehicle Routing Problems, main because it is the key problem of logistics distribution and communications and transportation, only has the scheduling problem of having solved just can make to provide and deliver effective and reasonable.
At present, the method that the research of domestic Vehicle Routing Problems is mainly used mainly contains following problem: the loading of all vehicle cargo is not considered the interconnection constraint having between goods.
Therefore, there is defect in existing Logistics Distribution Method, needs to improve.
During bicycle field, become when associated transport truck routing problem is considered to have speed simultaneously and become situation, and the situation of goods character interconnection constraint, to punish that the form of cost adds goods association in objective function.During bicycle field, becoming associated transport truck routing problem is an expansion of vehicle route, Vehicle Routing Problems has been the complete difficult problem of NP-, change while adding speed again, goods association, this problem is also a NP-Hard problem, this means when problem scale increases to some and will be difficult to or cannot try to achieve at all the globally optimal solution of problem.Although adopt exact algorithm to become associated transport truck routing problem can be to small-scale bicycle field time, obtain optimum solution, while not being suitable for the large-scale bicycle field solving in reality, become associated transport truck routing problem.Some scholar uses sequence Insertion heuristic algorithm to solve single Depot Vehicle Routing Problem, but for have multiple constraint bicycle field time become associated logistics transportation scheduling problem and be difficult to be suitable for.
Summary of the invention
The object of the invention is to the deficiency for above-mentioned prior art, proposed a kind of
while solving bicycle field, become the algorithm of associated transport truck routing problem, should
algorithm adoptschaos tabu search algorithm, to solve having the Vehicle Routing Problems of multiple constraint.
The method that becomes associated transport truck routing problem during the bicycle field of this comprises two-part content, (1) while setting up bicycle field, become the mathematical model of associated transport truck routing problem, total transportation cost of take is minimum is objective function, the association of freight hold is joined in the middle of objective function with the form of association punishment cost, the impact becoming while considering speed when considering maximum load constraint and ultimate range constraint, (2) for the optimizing of standard tabu search algorithm, rely on the problem of initial solution and neighborhood solution, use chaos optimization technology to generate initial solution, use various ways to generate neighborhood solution, improve the optimizing ability of algorithm.Its key step is as follows:
while solving bicycle field, become the algorithm of associated transport truck routing problem, should
algorithm adoptschaos tabu search algorithm, it comprises the following steps:
1) impact becoming while considering speed, joins the associated character of goods in the middle of objective function with the form of relevant cost, sets up mathematical model:
The impact that step 1) becomes while considering speed, joins the associated character of goods in the middle of objective function with the form of relevant cost, sets up mathematical model, and concrete steps are as follows:
Step 1.1: parking lot has
the name client that will serve, wherein the
individual client's the volume of goods transported is
(
=1,2 ...,
), goods need to be provided and delivered to client from parking lot, the dead weight of vehicle is known as
, known
<
, the vehicle number that we call needs is in advance estimated according to formula (1):
（1）
Wherein, [] representative is not more than the digital maximum positive integer in bracket;
the estimation to entrucking and the degree of difficulty of unloading and constraint,
;
Step 1.2: be defined as follows variable:
（2）
（3）
Set up objective function:
+
, the minimum of take dispensing expense is target, uses
expression is from client
to client
transportation cost,
=
, while considering speed, become factor, relevant cost, first is transportation cost, second is relevant cost,
represent to be loaded in the
the correlation coefficient of the freight hold on chassis, its value is larger, represents that the compatibility between goods is just better, and incompatible the produced expense of goods is just lower,
less, represent that compatibility between goods is just poorer, incompatible the produced expense of goods is just higher, and the 3rd is the fixing use cost of vehicle,
for the fixing use cost of separate unit car;
Step 1.3: set up inequality constrain:
（4）
（5）
（6）
（7）
(8)
(9)
(10)
Formula (4) represents the maximum of the distribution vehicle distance restraint that travels, in formula
represent client
to client
distance by vehicle
complete,
for vehicle
the customer service quantity of providing and delivering, is N to the maximum, and formula (5) and formula (6) have been set forth the relation between two variablees, and formula (7) represents that vehicle completes client
task after directly travel to client
it is provided and delivered, formula (8) retrained each client can only by a car serve and guarantee each client serviced to, formula (9) represents that the total weight of the goods of each car delivery cannot surpass the maximum load constraint of vehicle, and formula (10) guarantees that client's number that each car is provided and delivered can not surpass the total number of client;
Step 2) design a kind of chaos tabu search algorithm set up model is solved, select candidate solution to concentrate non-taboo
The optimum condition that object is corresponding is new current solution.
Further, concrete steps described step 2) are as follows:
Step 1: obtain distribution information from order ticket, described information comprises: thus the correlation coefficient of customer name, customer demand client aggregate demand, cumulative volume, freight hold, Traffic Information;
Step 2: obtain client's title from entrust waybill, inquire about client's position coordinates from speed storehouse, address, the distance between client;
Step 3: the parameter of setting chaos tabu search algorithm;
Step 4: by above-mentioned distribution information, customer address information, cargo requirement information, correlation coefficient information, car speed statistical information etc. is input in algorithm;
Step 5: according to client's number and demand, calculate required vehicle number, adopt the mode of natural integer to encode to each client;
Step 6: use chaos technology to produce and there is initial solution of overall importance
, taboo list is set to sky;
Step 7: whether evaluation algorithm end condition meets? if so, finish algorithm and export optimum results; Otherwise, continue following steps.
Step 8: neighborhood operation method, use between 2-0pt, path and exchange the some neighborhood solutions that produce current solution with insertion method, select some neighborhood solutions, form candidate's disaggregation;
Step 9: candidate solution is judged to whether despise criterion meets? if set up, with meeting the optimum condition of despising criterion
substitute
become new current solution,
, and use with
corresponding taboo object is replaced the taboo object that enters the earliest taboo list, uses simultaneously
" the best so far " state of replacement, then goes to step 11); Otherwise, continue following steps;
Step 10: the taboo attribute of each object that judgement candidate solution is corresponding, selecting candidate solution to concentrate optimum condition corresponding to non-taboo object is new current solution, replaces the taboo object elements that enters the earliest taboo list with corresponding with it taboo object simultaneously;
Step 11: go to step 7.
Further, the concrete steps of described step 6 are as follows:
Step 6.1, select Logistic chaotic maps initiation parameter:
（11）
Wherein:
be control variable, so, work as initial value
(0,1) and
=4 o'clock, the chaos state of the system tool that formula (11) represents in ergodicity optimum, so we can utilize him to produce chaos pseudo sequence, the probability density function of Logistic mapping is:
（12）
Lower boundary
; Coboundary
; The number of times that chaos random number produces is
; By test
be taken as at 3 o'clock and can reach and be uniformly distributed preferably effect; The scale-up factor that successively decreases on border is
, the probability density function according to Logistic mapping, is taken as 0,1,2, sets initial cycle times N=1; Initial chaos pseudo sequence length
;
Step 6.2, the random initial value that produces chaos pseudo sequence in interval (0,1)
(fixed point 0.25,0.5, except 0.75);
Step 6.3, iterative operation is carried out in application Logistic mapping, produces length and is
chaos random number sequence
, and be stored in sequence
in;
Step 6.4: application formula (12) is upgraded up-and-down boundary value,
（13）；
Step 6.5: the length of upgrading chaos pseudo sequence:
;
Step 6.6: judge whether to meet
, satisfied go to step 6.2; Otherwise go to step 6.7;
Step 6.7: output chaos pseudo sequence
; Finish algorithm.
Further, described step 8 specifically comprises the following steps:
Step 8.1, exchange in path: adopt 2-opt method two points of random selection in same path to exchange;
Step 8.2, exchanges between path and inserts: adopt and from path 1, select the stretch footpath of selecting in stretch footpath and path 2 to exchange, employing some paths from path 1 are inserted into before client's point of selecting in path 2.
Beneficial effect of the present invention is: while 1) setting up bicycle field, become the mathematical model of associated transport truck routing problem, the model of setting up more can reflect the actual conditions of logistics transport field vehicle route, makes the driving scheme based on this formulation more reliable; 2) take minimum run cost as target, make specified scheme have more economy.Of the present invention based on chaos tabu search
The method that becomes associated transport truck routing problem during the solving of algorithm can better solve the problems such as logistics transportation field is non-linear, multiple constraint, and can improve the dependence of standard tabu search algorithm to initial solution and neighborhood solution.
Accompanying drawing explanation:
Fig. 1 velocity profile;
Fig. 2 chaos tabu search algorithm realization flow figure;
Fig. 3: optimum distribution project trajectory diagram.
Embodiment:
Below in conjunction with accompanying drawing, the invention will be further described:
The method for solving that becomes associated transport truck path during the bicycle field based on chaos tabu search algorithm of the present invention comprises setting up to have multiple constraint, the vehicle route model of relevant cost; Initial solution based on Logistic mapping generates and the neighborhood solution based on various ways generates.
As shown in Figure 1, 2, 3,
while solving bicycle field, become the algorithm of associated transport truck routing problem, should
algorithm adoptschaos tabu search algorithm, its concrete implementation step is as follows:
The impact that step 1) becomes while considering speed, joins the associated character of goods in the middle of objective function with the form of relevant cost, sets up mathematical model, specifically comprises the following steps:
Step 1.1, the problem of the present invention research is based on following hypothesis:
(1) there is a parking lot,
client, and customer demand is known;
(2) closed type vehicle route;
(3) vehicle has maximum travel distance limit and undercapacity;
(4) vehicle has maximum load restriction;
(5) consider that goods character is associated.
(6) bundle of altering an agreement during speed, vehicle changes in the travel speed of each time period, can be lower than off-peak period at the car speed of peak period.Vehicle Speed piecewise function diagram as shown in Figure 1.
This parking lot has
the name client that will serve, wherein the
individual client's the volume of goods transported is
(
=1,2 ...,
), goods need to be provided and delivered to client from parking lot, the dead weight of vehicle is known as
, known
<
.The vehicle number that we call needs is in advance estimated according to formula (1).
（1）
Wherein, [] representative is not more than the digital maximum positive integer in bracket;
the estimation to entrucking and the degree of difficulty of unloading and constraint,
.
Step 1.2: be defined as follows variable:
（2）
（3）
Set up objective function
+
, the minimum of take dispensing expense is target, uses
expression is from client
to client
transportation cost,
=
, while considering speed, become factor, relevant cost.First is transportation cost, and second is relevant cost,
represent to be loaded in the
the correlation coefficient of the freight hold on chassis, its value is larger, represents that the compatibility between goods is just better, so, because incompatible the produced expense of goods is just lower,
less, represent that the compatibility between goods is just poorer, because incompatible the produced expense of goods is just higher.The 3rd is the fixing use cost of vehicle,
for the fixing use cost of separate unit car;
Step 1.3: set up inequality constrain:
（4）
（5）
（6）
（7）
(8)
(9)
(10)
Formula (4) represents the maximum of the distribution vehicle distance restraint that travels, in formula
represent client
to client
distance by vehicle
complete,
for vehicle
the customer service quantity of providing and delivering, is N to the maximum.Formula (5) and formula (6) have been set forth between two variablees
Relation.Formula (7) represents that vehicle completes client
task after directly travel to client
it is provided and delivered.Formula (8) retrained each client can only by a car serve and guarantee each client serviced to.Formula (9) represents that the total weight of the goods of each car delivery cannot surpass the maximum load constraint of vehicle.Formula (10) guarantees that client's number that each car is provided and delivered can not surpass the total number of client.
Step 2) design a kind of chaos tabu search algorithm set up model is solved, selecting candidate solution to concentrate optimum condition corresponding to non-taboo object is new current solution, described step 2) concrete steps as follows:
Step 1: obtain distribution information from order ticket, described information comprises: thus the correlation coefficient of customer name, customer demand client aggregate demand, cumulative volume, freight hold, Traffic Information;
Step 2: obtain client's title from entrust waybill, inquire about client's position coordinates from speed storehouse, address, the distance between client;
Step 3: the parameter of setting chaos tabu search algorithm;
Step 4: by above-mentioned distribution information, customer address information, cargo requirement information, correlation coefficient information, car speed statistical information etc. is input in algorithm;
Step 5: according to client's number and demand, calculate required vehicle number, adopt the mode of natural integer to encode to each client;
Step 6: use chaos technology to produce and there is initial solution of overall importance
, taboo list is set to sky;
Step 7: whether evaluation algorithm end condition meets? if so, finish algorithm and export optimum results; Otherwise, continue following steps.
Step 8: neighborhood operation method, use between 2-0pt, path and exchange the some neighborhood solutions that produce current solution with insertion method, select some neighborhood solutions, form candidate's disaggregation;
Step 9: candidate solution is judged to whether despise criterion meets? if set up, with meeting the optimum condition of despising criterion
substitute
become new current solution,
, and use with
corresponding taboo object is replaced the taboo object that enters the earliest taboo list, uses simultaneously
" the best so far " state of replacement, then goes to step 11); Otherwise, continue following steps;
Step 10: the taboo attribute of each object that judgement candidate solution is corresponding, selecting candidate solution to concentrate optimum condition corresponding to non-taboo object is new current solution, replaces the taboo object elements that enters the earliest taboo list with corresponding with it taboo object simultaneously;
Step 11: go to step 7.
In above-mentioned steps, the concrete steps of step 6 are as follows:
Step 6.1, selects Logistic chaotic maps initiation parameter: chaos is travelling of the exclusive a kind of aperiodic motion of nonlinear system, and it can show the behavior between random and rule, and its widespread use in all fields.Its inherent mechanism
Very exquisite, can, within the motion of system attraction and being strapped in certain scope, can travel through all states and there will not be repetition according to the rule of self.Here we select the most frequently used Logistic chaotic maps:
（11）
Wherein:
be control variable, so, work as initial value
(0,1) and
=4 o'clock, the chaos state of the system tool that formula (11) represents in ergodicity optimum, so we can utilize him to produce chaos pseudo sequence.The probability density function of Log istic mapping is:
（12）
The probability density distribution figure that reflects Logistic mapping from formula (12) is rare in the middle of should being, edge is close, and (0,1) in interval, be symmetrical centered by 0.5, feature in view of Logistic chaotic maps, in order to access equally distributed chaos stochastic distribution, thereby improve the ability of searching optimum of chaos tabu search algorithm,, the producing method of above-mentioned chaos pseudo sequence is improved.Only with the production method of one dimension chaos pseudo sequence, introduced below.Its concrete steps are as follows:
Initiation parameter: lower boundary
; Coboundary
; The number of times that chaos random number produces is
; By test
be taken as at 3 o'clock and can reach and be uniformly distributed preferably effect; The scale-up factor that successively decreases on border is
, the probability density function according to Logistic mapping, is taken as 0,1,2, sets initial cycle times N=1; Initial chaos pseudo sequence length
;
Step 6.2, the random initial value that produces chaos pseudo sequence in interval (0,1)
(fixed point 0.25,0.5, except 0.75);
Step 6.3, iterative operation is carried out in application Logistic mapping, produces length and is
chaos random number sequence
, and be stored in sequence
in.
Step 6.4, application formula (12) is upgraded up-and-down boundary value,
（13）
Step 6.5, the length of renewal chaos pseudo sequence:
;
Step 6.6, judges whether to meet
, satisfied go to step 3.6.2; Otherwise go to step 6.7.
Step 6.7: output chaos pseudo sequence
; Finish algorithm.
Neighborhood operation method in described step 8: use between 2-0pt, path and exchange the some neighborhood solutions that produce current solution with insertion method, select some neighborhood solutions, form candidate's disaggregation.
Concrete steps are as follows:
Step 8.1: exchange in path.Adopt 2-opt method two points of random selection in same path to exchange, as: the path 0-1-3-5-2-0 of certain car, produce at random two number clearing houses and become new explanations, as exchange 1 and 2 two point, obtain new path 0-2-3-5-1-0.
Step 8.2: exchange and insertion between path.Employing selects the stretch footpath of selecting in stretch footpath and path 2 to exchange from path 1, as: the vehicle route of certain car is 0-1-3-5-2 – 0, the vehicle route of another car is 0-6-7-0, the new explanation 0-6-5-2-0 that clearing house becomes, 0-1-3-7-0, rearranges vehicle.Employing some paths from path 1 are inserted into before client's point of selecting in path 2, as: a vehicle route is 0-1-3-5-2-0, and another vehicle route is 0-6-7-0, the new explanation 0-1-5-2-0 that clearing house becomes, 0-6-3-7-0, rearranges vehicle.
Effect of the present invention can further illustrate by following emulation:
1: simulated conditions
(1) unit dispensing expense is 1 yuan/km, and vehicle is reinstated cost and is fixed as 100 yuan.Be 7:00 the time of departure the earliest.
(2) emulated data: customer information is as shown in table 1.
Table 1 customer information
Table 2 goods correlation coefficient
(2) simulation parameter:
Case Simulation in this chapter is on the PC of Intel (R) Pentium CPU2.53GHz, internal memory 2.0G, to adopt Microsoft Visual C++6.0 programming to realize.The iterative steps of set algorithm is 200 steps, 20 neighborhood solutions of the current solution of iterative search each time, and setting Tabu Length is 15.With chaos tabu search algorithm, solve at random, obtain result of calculation.
2 emulation contents
Use and mix tabu search algorithm, the minimum dispensing expense of take is optimization aim, and in his-and-hers watches 1, client's requirement solves, and draws optimal path.Record client's situation of providing and delivering.Show that optimum dispensing situation is as shown in table 3.
The optimum distribution route of table 3
3. simulation analysis
From simulation result, through iteration, algorithm is finally restrained, and draws optimum distribution project.Gross vehicle dispensing expense is 1141.81 yuan.
What more than set forth is the excellent results that embodiment shows that the present invention provides.
Claims (4)
1. while solving bicycle field, become an algorithm for associated transport truck routing problem, this algorithm adopts chaos tabu search algorithm, it is characterized in that, it comprises the following steps:
The impact that step 1) becomes while considering speed, joins the associated character of goods in the middle of objective function with the form of relevant cost, sets up mathematical model, and concrete steps are as follows:
Step 1.1: parking lot has
the name client that will serve, wherein the
individual client's the volume of goods transported is
(
=1,2 ...,
), goods need to be provided and delivered to client from parking lot, the dead weight of vehicle is known as
, known
<
, the vehicle number that we call needs is in advance estimated according to formula (1):
（1）
Wherein, [] representative is not more than the digital maximum positive integer in bracket;
the estimation to entrucking and the degree of difficulty of unloading and constraint,
;
Step 1.2: be defined as follows variable:
（2）
（3）
Set up objective function:
+
, the minimum of take dispensing expense is target, uses
expression is from client
to client
transportation cost,
=
, while considering speed, become factor, relevant cost, first is transportation cost, second is relevant cost,
represent to be loaded in the
the correlation coefficient of the freight hold on chassis, its value is larger, represents that the compatibility between goods is just better, and incompatible the produced expense of goods is just lower,
less, represent that compatibility between goods is just poorer, incompatible the produced expense of goods is just higher, and the 3rd is the fixing use cost of vehicle,
for the fixing use cost of separate unit car;
Step 1.3: set up inequality constrain:
（4）
（5）
（6）
（7）
(8)
(9)
(10)
Formula (4) represents the maximum of the distribution vehicle distance restraint that travels, in formula
represent client
to client
distance by vehicle
complete,
for vehicle
the customer service quantity of providing and delivering, is N to the maximum, and formula (5) and formula (6) have been set forth the relation between two variablees, and formula (7) represents that vehicle completes client
task after directly travel to client
it is provided and delivered, formula (8) retrained each client can only by a car serve and guarantee each client serviced to, formula (9) represents that the total weight of the goods of each car delivery cannot surpass the maximum load constraint of vehicle, and formula (10) guarantees that client's number that each car is provided and delivered can not surpass the total number of client;
Step 2) design a kind of chaos tabu search algorithm set up model is solved, selecting candidate solution to concentrate optimum condition corresponding to non-taboo object is new current solution.
2. a kind of algorithm that becomes associated transport truck routing problem while solving bicycle field according to claim 1, is characterized in that described step 2) concrete steps as follows:
Step 1: obtain distribution information from order ticket, described information comprises: thus the correlation coefficient of customer name, customer demand client aggregate demand, cumulative volume, freight hold, Traffic Information;
Step 2: obtain client's title from entrust waybill, inquire about client's position coordinates from speed storehouse, address, the distance between client;
Step 3: the parameter of setting chaos tabu search algorithm;
Step 4: by above-mentioned distribution information, customer address information, cargo requirement information, correlation coefficient information, car speed statistical information etc. is input in algorithm;
Step 5: according to client's number and demand, calculate required vehicle number, adopt the mode of natural integer to encode to each client;
Step 6: use chaos technology to produce and there is initial solution of overall importance
, taboo list is set to sky;
Step 7: whether evaluation algorithm end condition meets? if so, finish algorithm and export optimum results; Otherwise, continue following steps;
Step 8: neighborhood operation method, use between 2-0pt, path and exchange the some neighborhood solutions that produce current solution with insertion method, select some neighborhood solutions, form candidate's disaggregation;
Step 9: candidate solution is judged to whether despise criterion meets? if set up, with meeting the optimum condition of despising criterion
substitute
become new current solution,
, and use with
corresponding taboo object is replaced the taboo object that enters the earliest taboo list, uses simultaneously
" the best so far " state of replacement, then goes to step 11); Otherwise, continue following steps;
Step 10: the taboo attribute of each object that judgement candidate solution is corresponding, selecting candidate solution to concentrate optimum condition corresponding to non-taboo object is new current solution, replaces the taboo object elements that enters the earliest taboo list with corresponding with it taboo object simultaneously;
Step 11: go to step 7.
3. the algorithm that becomes associated transport truck routing problem while solving bicycle field according to one kind of claim 2, is characterized in that, the concrete steps of described step 6 are as follows:
Step 6.1, select Logistic chaotic maps initiation parameter:
（11）
Wherein:
be control variable, so, work as initial value
(0,1) and
=4 o'clock, the chaos state of the system tool that formula (11) represents in ergodicity optimum, so we can utilize him to produce chaos pseudo sequence, the probability density function of Log istic mapping is:
（12）
Lower boundary
; Coboundary
; The number of times that chaos random number produces is
; By test
be taken as at 3 o'clock and can reach and be uniformly distributed preferably effect; The scale-up factor that successively decreases on border is
, the probability density function according to Logistic mapping, is taken as 0,1,2, sets initial cycle times N=1; Initial chaos pseudo sequence length
;
Step 6.2, the random initial value that produces chaos pseudo sequence in interval (0,1)
(fixed point 0.25,0.5, except 0.75);
Step 6.3, iterative operation is carried out in application Logistic mapping, produces length and is
chaos random number sequence
, and be stored in sequence
in;
Step 6.4: application formula (12) is upgraded up-and-down boundary value,
（13）；
Step 6.5: the length of upgrading chaos pseudo sequence:
;
Step 6.6: judge whether to meet
, satisfied go to step 6.2; Otherwise go to step 6.7;
Step 6.7: output chaos pseudo sequence
; Finish algorithm.
4. the algorithm that becomes associated transport truck routing problem while solving bicycle field according to one kind of claim 2, is characterized in that, described step 8 specifically comprises the following steps:
Step 8.1, exchange in path: adopt 2-opt method two points of random selection in same path to exchange;
Step 8.2, exchanges between path and inserts: adopt and from path 1, select the stretch footpath of selecting in stretch footpath and path 2 to exchange, employing some paths from path 1 are inserted into before client's point of selecting in path 2.
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| CN109711599A (en) * | 2018-11-26 | 2019-05-03 | 跨越速运集团有限公司 | Based on the preferential material flows automation dispatching method of timeliness and system |
| CN109857937A (en) * | 2019-01-25 | 2019-06-07 | 同济大学 | One kind being based on Sine mapping and segmented continuous TABU search data processing method parallel |
| CN110008546B (en) * | 2019-03-22 | 2022-07-19 | 西南交通大学 | Circular passageway facility arrangement method |
| CN110008546A (en) * | 2019-03-22 | 2019-07-12 | 西南交通大学 | Circular passageway facility method for arranging |
| CN110428089A (en) * | 2019-07-03 | 2019-11-08 | 广东工业大学 | Method, system and the equipment of a kind of bicycle field logistics transportation scheduling |
| CN110428089B (en) * | 2019-07-03 | 2022-09-13 | 广东工业大学 | Method, system and equipment for logistics transportation scheduling of bicycle yard |
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| CN111985700A (en) * | 2020-07-30 | 2020-11-24 | 中国外运股份有限公司 | Vehicle carrying single quantity balancing method and device for determining home delivery and loading |
| CN111985700B (en) * | 2020-07-30 | 2024-01-05 | 中国外运股份有限公司 | Vehicle carrying bill quantity balancing method and device for determining home delivery |
| CN112235216A (en) * | 2020-10-16 | 2021-01-15 | 哈尔滨工程大学 | Compressed sensing pilot frequency design method based on tabu search |
| CN113393111A (en) * | 2021-06-09 | 2021-09-14 | 东南大学 | Cross-border transportation bilateral connection vehicle scheduling method based on variable neighborhood tabu search algorithm |
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