CN108921467A - The intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic - Google Patents

The intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic Download PDF

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CN108921467A
CN108921467A CN201810621949.1A CN201810621949A CN108921467A CN 108921467 A CN108921467 A CN 108921467A CN 201810621949 A CN201810621949 A CN 201810621949A CN 108921467 A CN108921467 A CN 108921467A
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郑家佳
白晓辉
谷振宇
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Chongqing City Management College
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Abstract

The present invention relates to logistics technology, specially a kind of intelligent body decentralized dispatch method that addressee information customer demand is changed towards dynamic includes the following steps：1) intelligent body dispensing vehicle receives dynamic customer order information；2) intelligent body dispensing vehicle carries out decentralized dispatch according to its position and remaining task situation combination dynamic customer demand.The present invention is changed to the existing mode for carrying out subjective scheduling by dispatching person to carry out the mode of decentralized dispatch respectively by each intelligent body distribution vehicle, when client changes information on services, by in way intelligent body dispensing vehicle according to its position and remaining task situation, in conjunction with dynamic customer demand, the scheme that achieves a solution is operated by the genetic algorithm of insertion algorithm and dual threshold control, the optimal solution for dynamic customer demand quickly can be reasonably made, reduces the side effect of disturbance to the maximum extent.

Description

The intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic
Technical field
The present invention relates to logistics technology, specially a kind of express mail distribution scheduling method.
Background technique
As the application of China's mobile communication technology and Internet technology becomes increasingly popular and perfect, the shopping way of resident Very big variation is produced, the online shopping under e-commerce environment receives the very big welcome of consumer.Survey data shows, The China's online-shopping market B2C transaction size in 2017 increased by 29.6% compared with 2016 up to 6.1 trillion yuans.It expects 2021, The Chinese online-shopping market B2C scale will be more than 10 trillion yuans.Currently, China has been surpassed using the customer count of shopping at network 4.9 hundred million people are crossed, the netizen for having more than 66.4% joined shopping at network ranks.Express delivery is the basis of e-commerce, electronics quotient To delivery industry, more stringent requirements are proposed for the rapid development of business, how to improve Courier Service level and has become e-commerce field New challenge.According to statistics, the express delivery quantity of whole year in 2017, the processing of China's delivery industry reach 400.6 hundred million, increase by a year-on-year basis 28.1%.It is sure to occupy the first in the world within Chinese Express Service market scale continuous 3 years, it is average to need to handle 1.09 hundred million express deliveries daily.Fastly The important component that industry is service trade is passed, is had a very important role for the development of e-commerce industry." last is public In " dispatching, the end as express delivery dispenses link, since the customer quantity of service is numerous, position disperses, demand is different, Generally existing distribution cost is high, dispatching poor in timeliness, dispenses the problems such as failure rate is high for the first time, this seriously constrains e-commerce production The sane development of industry.Appropriate " last one kilometer " express mail distribution project is formulated, provides decision support for dispatching line optimization, it is right In reducing distribution cost, improves dispatching efficiency and customer satisfaction is of great significance.
It dispenses on the way, is in due to client in the uncertain environment of height, there are various need in " last one kilometer " express delivery The dynamic customer of addressee information is changed, including：When rejecting the client of order, the client for changing posting address and change addressee Between client.When occur change addressee information dynamic customer when, it will cause the distribution project being carrying out no longer it is optimal very It is extremely infeasible, so that system is become abnormal.The person of sending with charge free needs to adjust scheduled distribution project in real time according to customer demand, quickly rationally The solution for dynamic customer demand is made on ground, reduces the side effect of disturbance to the maximum extent, it has also become express delivery industry is anxious Problem to be solved.Currently, when there is the dynamic customer of change addressee information, artificial decision is mainly carried out by dispatching person, it is this Mode is subjective random very big, has certain blindness, cannot scientifically and accurately cook up new distribution project, not only waste Resource is dispensed, and also causes dispatching failure rate for the first time and remains high.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of intelligent bodies for changing addressee information customer demand towards dynamic Decentralized dispatch method, realization rationally effectively handle dynamic customer.
In order to achieve the above objectives, the present invention provides the following technical solutions：
The intelligent body decentralized dispatch method that addressee information customer demand is changed towards dynamic, includes the following steps：
1) intelligent body dispensing vehicle receives dynamic customer order information；
2) intelligent body dispensing vehicle carries out dispersion tune according to its position and remaining task situation combination dynamic customer demand Degree.
Further, dynamic customer order includes when rejecting order, change posting address and change addressee in the step 1) Between 3 kinds of dynamic customer demands.
Further, the step 2) specifically comprises the following steps：
21) when dynamic customer demand is to reject order, the client is deleted from current distribution project and is jumped execute step It is rapid 24)；
22) it when dynamic customer demand is change posting address or change addressee time, is deleted in current distribution project The client simultaneously updates information on services, and time window is set as hard time window, then executes step 23)；
23) on the basis of former distribution project, after solving by insertion algorithm, the part for meeting dynamic customer demand is obtained Optimal solution；
24) after solving by the genetic algorithm that dual threshold controls, the All Optimal Solutions for meeting dynamic customer demand are obtained；
25) optimal solution obtained according to step 24), obtains the distribution project of update.
Further, the step 23) specifically comprises the following steps：
231) it performs the encoding operation, home-delivery center is encoded to 0, N number of static client is successively encoded to 1,2,3 ..., N, M dynamic customer is successively encoded to N+1, N+2 ..., N+M, wherein (N+M) is current dynamic customer；
232) it calculates separately out dynamic customer (N+M) insertion client path [i] and path [i+1] (i=0,1 ..., (N + M-2)) between after increased operating range Δ s [i]：
Δ s [i]=dPath [i], N+M+dN+M, path [i+1]-dPath [i], path [i+1]；
233) a minimum value Δ s [m] is chosen from Δ s [i], so that Δ s [m]≤Δ s [i], wherein m ∈ [0, N+M- 2], i=0,1,2 ..., (N+M-2), corresponding client path [m] and client path [m+1] they are current best insertion position It sets；
234) judge whether Δ s [m] is T；If Δ s [m] is equal to T, going to step 226) terminates insertion algorithm operation；
235) judge whether the hard time window of dynamic customer N+M meets the requirements；Reach the time t of client N+MN+MFor：
tN+M=tpath[m]+max[(apath[m]-tpath[m]), 0]+fpath[m]+tPath [m], N+M·dPath [m], N+M
If aN+1≤tN+1≤bN+1, then the time window of the dynamic customer is met the requirements, and obtains initial optimal solution；Otherwise it is discontented with Foot requires, and enables Δ s [m]=T, turns again to step 223)；
236) terminate insertion algorithm operation.
Further, the step 24) specifically comprises the following steps：
241) home-delivery center is encoded to 0, N number of static client is successively encoded to 1,2,3 ..., N, by M dynamic customer Successively it is encoded to N+1, N+2 ..., N+M；Each individual in population is initialized；
242) fitness function is designed, and calculates the fitness value of each individual in population；
243) selection operator operation is carried out, is according to being ranked up to individual, according to setting in advance with the fitness value of individual The select probability p setsFor ratio, the individual for replacing fitness poor with the preferable individual of fitness；
244) judge whether to meet algorithm termination condition；If satisfied, the optimal solution of optimum individual and its representative is then exported, and Stop calculating；Otherwise it turns to and 245) continues iteration.；
245) the execution time that mutation operation is adjusted by former generation's similarity threshold makes a variation general by degree of convergence adjusting thresholds Rate；Mutation operation is carried out using reverse mutation operator；
246) according to preset crossover probability, more former generation's crossover operations are carried out；
247) it by obtaining population of new generation after above-mentioned intersection and mutation operator operation, and returns 242).
Further, the step 25) specifically comprises the following steps：
Judge whether the hard time window of each dynamic customer in new distribution project meets the requirements：Known arrival client path [i] Time be tpath[i], then the time that can be calculated up to client path [i+1] is：
tpath[i+1]=tpath[i]+max[(apath[i]-tpath[i]), 0]+fpath[i]+tPath [i], path [i+1]· dPath [i], path [i+1]；
Distribution project is updated if the hard time window of all dynamic customers is all met the requirements, and terminates to change at addressee information Reason；Otherwise, which is made into rejection order processing.
Further, the step 23) and 24) in, the superiority and inferiority that currently solves is evaluated by following formula：
In above formula, min A is distribution cost, and min B is rejection penalty,β is weight coefficient,β ∈ [0, 1],
In above formula：
N:The static client sum not serviced also；
M:The dynamic customer sum not serviced also；
C:The expense of dispensing vehicle traveling unit distance；
dI, j:Distance of the client i to client j；
pj:The expense of j-th of client unit quality unloading or loading；
mi:The weight of client's i express delivery；
lti:Delay the length of time for reaching client's point i；
l:For weak rock mass client, dispensing vehicle delays to reach the penalty value of unit time；
T:10000*l。
The beneficial effects of the present invention are：The existing mode for carrying out subjective scheduling by dispatching person is changed to by each by the present invention Intelligent body distribution vehicle carries out the mode of decentralized dispatch respectively, when client changes information on services, by way intelligent body dispensing vehicle Pass through the legacy of insertion algorithm and dual threshold control in conjunction with dynamic customer demand according to its position and remaining task situation Algorithm operating achieves a solution scheme, quickly can reasonably make the optimal solution for dynamic customer demand, maximum limit Reduce the side effect of disturbance in degree ground.
Detailed description of the invention
In order to keep the purpose of the present invention, technical scheme and beneficial effects clearer, the present invention provides following attached drawing：
Fig. 1 is flow diagram of the invention；
Fig. 2 is the insertion algorithm operational flowchart in embodiment；
Fig. 3 is the operatings of genetic algorithm flow chart of the dual threshold control in embodiment；
Fig. 4 is the Static route figure of intelligent body distribution vehicle in embodiment；
Fig. 5 is the solution that when the dynamic customer change addressee time, intelligent body dispensing vehicle application this method is got in embodiment Certainly scheme.
Specific embodiment
Below in conjunction with attached drawing, a preferred embodiment of the present invention will be described in detail, but illustrated embodiment not as Limitation of the invention.
Referring to Fig. 1, the intelligent body decentralized dispatch method that addressee information customer demand is changed towards dynamic of the present embodiment, packet Include following steps：
1) intelligent body dispensing vehicle receives dynamic customer order information；Dynamic customer order information includes rejecting order, change Posting address and change 3 kinds of dynamic customer demands of addressee time.
2) intelligent body dispensing vehicle carries out dispersion tune according to its position and remaining task situation combination dynamic customer demand Degree.Specifically comprise the following steps：
21) when dynamic customer demand is to reject order, the client is deleted from current distribution project and is jumped execute step It is rapid 24)；
22) it when dynamic customer demand is change posting address or change addressee time, is deleted in current distribution project The client simultaneously updates information on services, and time window is set as hard time window, then executes step 23)；
23) information on services such as address, time window of each client in intelligent body are inputted, on the basis of former distribution project, are led to Insertion algorithm operation is crossed, the locally optimal solution for meeting dynamic customer demand is obtained；Referring to fig. 2, specifically comprise the following steps：
231) it performs the encoding operation, home-delivery center is encoded to 0, N number of static client is successively encoded to 1,2,3 ..., N, M dynamic customer is successively encoded to N+1, N+2 ..., N+M, wherein (N+M) is current dynamic customer；
232) it calculates separately out dynamic customer (N+M) insertion client path [i] and path [i+1] (i=0,1 ..., (N+ M-2 increased operating range Δ s [i] after between))：
Δ s [i]=dPath [i], N+M+dN+M, path [i+1]-dpath[i], dpath[i+1]；
233) a minimum value Δ s [m] is chosen from Δ s [i], so that Δ s [m]≤Δ s [i], wherein m ∈ [0, N+M- 2], i=0,1,2 ..., (N+M-2), corresponding client path [m] and client path [m+1] they are current best insertion position It sets；
234) judge whether Δ s [m] is T；If Δ s [m] is equal to T, going to step 226) terminates insertion algorithm operation； 235) judge whether the hard time window of dynamic customer N+M meets the requirements；Reach the time t of client N+MN+MFor：
tN+M=tpath[m]+max[(apath[m]-tpath[m]), 0]+fpath[m]+tPath [m], N+M·dPath [m], N+M
If aN+1≤tN+1≤bN+1, then the time window of the dynamic customer is met the requirements, and obtains initial optimal solution；Otherwise it is discontented with Foot requires, and enables Δ s [m]=T, turns again to step 223)；
236) terminate insertion algorithm operation.
24) information on services such as address, time window of each client in intelligent body, the genetic algorithm controlled by dual threshold are inputted Operation obtains the globally optimal solution for meeting dynamic customer demand；Referring to Fig. 3, specifically comprise the following steps：
241) home-delivery center is encoded to 0, N number of static client is successively encoded to 1,2,3 ..., N, by M dynamic customer Successively it is encoded to N+1, N+2 ..., N+M；Each individual in population is initialized；
242) fitness function is designed, and calculates the fitness value of each individual in population；
243) selection operator operation is carried out, is according to being ranked up to individual, according to setting in advance with the fitness value of individual The select probability p setsFor ratio, the individual for replacing fitness poor with the preferable individual of fitness；
244) judge whether to meet algorithm termination condition；If satisfied, the optimal solution of optimum individual and its representative is then exported, and Stop calculating；Otherwise it turns to and 245) continues iteration.；
245) the execution time that mutation operation is adjusted by former generation's similarity threshold makes a variation general by degree of convergence adjusting thresholds Rate；Mutation operation is carried out using reverse mutation operator；
246) according to preset crossover probability, more former generation's crossover operations are carried out；
247) it by obtaining population of new generation after above-mentioned intersection and mutation operator operation, and returns 242).
25) optimal solution obtained according to step 24), obtains the distribution project of update, specifically includes
Judge whether the hard time window of each dynamic customer in new distribution project meets the requirements：Known arrival client path [i] Time be tpath[i], then the time that can be calculated up to client path [i+1] is：
tpath[i+1]=tpath[i]+max[(apath[i]-tpath[i]), 0]+fpath[i]+tPath [i], path [i+1]· dPath [i], path [i+1]；
Distribution project is updated if the hard time window of all dynamic customers is all met the requirements, and terminates to change at addressee information Reason；Otherwise, which is made into rejection order processing.
In the present embodiment, judge whether hard time window meets the requirements by decentralized dispatch model：
The model is described as follows：There is an end home-delivery center, the area which is serviced is divided by street Multiple zonules, home-delivery center sort express delivery according to the region of division, each intelligent body dispensing vehicle is responsible for a cell The express delivery in the domain service of fetching and delivering.Each dispensing vehicle successively services each client's point, returns and match after completion task from home-delivery center Send center.When intelligent body dispensing vehicle sets out, the static client serviced it formulates optimization distribution project, is meeting all constraint items Under part, so that being optimal using distribution cost and rejection penalty as the evaluation function of Bi-objective；In the delivery process of express delivery, to Services client is subject to variation addressee information, at this point, by way intelligent body dispensing vehicle according to its position and remaining task situation, Decentralized dispatch is carried out in conjunction with dynamic customer demand, realization reasonably handles dynamic customer.
Constraint condition：
1. the dead weight of dispensing vehicle is Q, the quality of all express deliveries may not exceed Q on dispensing vehicle；
2. the maximum volume of dispensing vehicle is V, the volume of all express deliveries may not exceed V on dispensing vehicle；
3. service time window：Requirement according to client to timeliness, when setting soft for the service time window of static client Between window, set hard time window for the service time window of dynamic customer.
Symbol description：
[ai,bi]:The service time window of client i.
N:The static client sum not serviced also.It is 0 by home-delivery center's number, is by static client's number consecutively：1,2, 3 ..., N.
M:The dynamic customer sum not serviced also.It is by dynamic customer number：N+1, N+2 ..., N+M.
C:The expense of dispensing vehicle traveling unit distance.
dI, j:Distance of the client i to client j.
tI, j:Time needed for road driving unit distance from client i to client j.
pj:The expense of j-th of client unit quality unloading or loading.
mi:The weight of client's i express delivery.
vi:The volume of client's i express delivery.
ti:The time of dispensing vehicle arrival client i.
wti:The length of time of client's point i is reached in advance.
lti:Delay the length of time for reaching client's point i.
fi:Service time needed for client i.
l:For weak rock mass client, dispensing vehicle delays to reach the penalty value of unit time.
T:10000*l。
If the known time for reaching client's point i is ti, then the time t that client j is reached from client i can be obtainedjFor：
tj=ti+wti+fi+fI, j·dI, j 　　(1)
The length of time of arrival client's point j is in advance：wtj=max [(aj-tj), 0] (2)
Delay reach client's point j length of time be：ltj=max [(tj-bj), 0] (3)
Objective function one：Distribution cost min A.
Distribution cost consists of two parts.First part is the run cost of dispensing vehicle, and second part is service fee.
Objective function two：Rejection penalty min B.
In this model, hard time window is set by the time window of dynamic customer, dispensing vehicle must be before the deadline Offering customers service；Weak rock mass is set by the time window of static client, dispensing vehicle should be as far as possible within the scope of time window to quiet State offering customers service can reach in advance and also delay arrival, but when delaying arrival, need to receive and delay that reach duration directly proportional Punishment.Customer satisfaction min B is for identifying the rejection penalty delayed to reach.
Evaluation function：
The model is simultaneously with distribution cost and the minimum evaluation function of rejection penalty, according to the important of the two objective functions Degree assigns different weights respectively
S.T:
Objective function (4) indicates the distribution cost of distribution vehicle, and distribution cost is mainly by transportation cost and dress landed cost Composition；Objective function (5) indicates that the active service time is later than rejection penalty caused by the stipulated time；Evaluation function (6) indicates total Dispatching expense, for the optimization aim of the model.Constraint condition (7) indicates that current N+M client o'clock is gone to take by a dispensing vehicle Business；Constraint condition (8) indicates that each client's point must service；Constraint condition (9) indicates distribution vehicle from dispatching The heart sets out and finally returns that home-delivery center；Weight of the cargo that constraint condition (10) expression distribution vehicle is transported no more than vehicle Amount limitation；Volumetric constraint of the cargo that constraint condition (11) expression distribution vehicle is transported no more than vehicle；Constraint condition (12) it is N+M that indicate also needs the client's number serviced in total.
For this example using some intelligent body dispensing vehicle as research object, the relevant parameter of the dispensing vehicle is as shown in table 1.Assuming that At certain moment of dispatching on the way, original dispatching route of static client's point is not as shown in figure 4, also surplus 9 static client's points carry out It services (being virtually home-delivery center by dispensing vehicle current location), at this point, if client 1 needs to change addressee time window by [4,12] It can get solution as shown in Figure 5 after intelligent body dispensing vehicle processing for [60,80].Wherein, between each client away from From as shown in table 2；The relevant parameter of each client's point is as shown in table 3；Other relevant parameters are as shown in table 4.
1 distribution vehicle relevant parameter of table
Distance d between each client of table 2I, j
3 client's relevant parameter of table
Other relevant parameters of table 4
Finally, it is stated that preferred embodiment above is only used to illustrate the technical scheme of the present invention and not to limit it, although logical It crosses above preferred embodiment the present invention is described in detail, however, those skilled in the art should understand that, can be Various changes are made to it in form and in details, without departing from claims of the present invention limited range.

Claims (7)

1. changing the intelligent body decentralized dispatch method of addressee information customer demand towards dynamic, it is characterised in that including walking as follows Suddenly：
1) intelligent body dispensing vehicle receives dynamic customer order information；
2) intelligent body dispensing vehicle carries out decentralized dispatch according to its position and remaining task situation combination dynamic customer demand.
2. the intelligent body decentralized dispatch method according to claim 1 that addressee information customer demand is changed towards dynamic, It is characterized in that, dynamic customer order includes rejecting order, change posting address and changing 3 kinds of the addressee time to move in the step 1) State customer demand.
3. the intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic as claimed in claim 2, it is special Sign is：The step 2) specifically comprises the following steps：
21) when dynamic customer demand is to reject order, the client is deleted from current distribution project and jumps execution step 24)；
22) when dynamic customer demand is change posting address or change addressee time, the visitor is deleted in current distribution project Family simultaneously updates information on services, and time window is set as hard time window, then executes step 23)；
23) on the basis of former distribution project, after solving by insertion algorithm, the local optimum for meeting dynamic customer demand is obtained Solution；
24) after solving by the genetic algorithm that dual threshold controls, the All Optimal Solutions for meeting dynamic customer demand are obtained；
25) optimal solution obtained according to step 24), obtains the distribution project of update.
4. the intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic as claimed in claim 3, it is special Sign is：The step 23) specifically comprises the following steps：
231) it performs the encoding operation, home-delivery center is encoded to 0, N number of static client is successively encoded to 1,2,3 ..., N, by M Each and every one dynamic customer is successively encoded to N+1, N+2 ..., N+M, wherein (N+M) is current dynamic customer；
232) it calculates separately out dynamic customer (N+M) insertion client path [i] and path [i+1] (i=0,1 ..., (N+M- 2) increased operating range Δ s [i] after between)：
Δ s [i]=dPath [i], N+M+dN+M, path [i+1]-dPath [i], path [i+1]；
233) a minimum value Δ s [m] is chosen from Δ s [i], so that Δ s [m]≤Δ s [i], wherein m ∈ [0, N+M-2], i =0,1,2 ..., (N+M-2), corresponding client path [m] and client path [m+1] are current best insertion position；
234) judge whether Δ s [m] is T；If Δ s [m] is equal to T, going to step 226) terminates insertion algorithm operation；
235) judge whether the hard time window of dynamic customer n+M meets the requirements；Reach the time t of client n+MN+MFor：
tN+M=tpath[m]+max[(apath[m]-tpath[m]), 0]+fpath[m]+tPath [m], N+M·dPath [m], N+M
If aN+1≤tN+1≤bN+1, then the time window of the dynamic customer is met the requirements, and obtains initial optimal solution；Otherwise it is unsatisfactory for wanting It asks, enables Δ s [m]=T, turn again to step 223)；
236) terminate insertion algorithm operation.
5. the intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic as claimed in claim 3, it is special Sign is：The step 24) specifically comprises the following steps：
241) home-delivery center is encoded to 0, N number of static client is successively encoded to 1,2,3 ..., N, successively by M dynamic customer It is encoded to N+1, N+2 ..., N+M；Each individual in population is initialized；
242) fitness function is designed, and calculates the fitness value of each individual in population；
243) selection operator operation is carried out, is according to being ranked up to individual, according to being previously set with the fitness value of individual Select probability psFor ratio, the individual for replacing fitness poor with the preferable individual of fitness；
244) judge whether to meet algorithm termination condition；If satisfied, then exporting the optimal solution of optimum individual and its representative, and stop It calculates；Otherwise it turns to and 245) continues iteration.；
245) the execution time that mutation operation is adjusted by former generation's similarity threshold, by degree of convergence adjusting thresholds mutation probability；Make Mutation operation is carried out with reverse mutation operator；
246) according to preset crossover probability, more former generation's crossover operations are carried out；
247) it by obtaining population of new generation after above-mentioned intersection and mutation operator operation, and returns 242).
6. the intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic as claimed in claim 3, it is special Sign is：The step 25) specifically comprises the following steps：
Judge whether the hard time window of each dynamic customer in new distribution project meets the requirements：It is known reach client path [i] when Between be tpath[i], then the time that can be calculated up to client path [i+1] is：
tpath[i+1]=tpath[i]+max[(apath[i]-tpath[i]), 0]+fpath[i]+tPath [i], path [i+1]·dPath [i], path [i+1]；
Distribution project is updated if the hard time window of all dynamic customers is all met the requirements, and terminates to change addressee information processing； Otherwise, which is made into rejection order processing.
7. the intelligent body decentralized dispatch method of addressee information customer demand is changed towards dynamic as claimed in claim 3, it is special Sign is：The step 23) and 24) in, the superiority and inferiority that currently solves is evaluated by following formula：
In above formula, min A is distribution cost, and min B is rejection penalty,β is weight coefficient,
In above formula：
N:The static client sum not serviced also；
M:The dynamic customer sum not serviced also；
C:The expense of dispensing vehicle traveling unit distance；
dI, j:Distance of the client i to client j；
pj:The expense of j-th of client unit quality unloading or loading；
mi:The weight of client's i express delivery；
lti:Delay the length of time for reaching client's point i；
l:For weak rock mass client, dispensing vehicle delays to reach the penalty value of unit time；
T:10000*l。
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