CN109961221A - A kind of Direct Distribution Time Dependent is in the parallel machine dispatching method in machine geographical location - Google Patents
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Abstract
The present invention provides a kind of Direct Distribution Time Dependent in the parallel machine dispatching method in machine geographical location, do not consider the problems of that the Direct Distribution time has changeability the existing dispatching method intended to solve, the solution obtained using MEST algorithm is as initial solution, number of jobs in conjunction with exchange transformation and insertion transformation to change in sub- scheduling, and by short job priority and first processing rule realization production scheduling sequence is arrived first, solve influence of the changeability of Direct Distribution time to parallel machine dispatching method solution.Parallel machine dispatching method proposed by the present invention, satisfied production scheduling can be obtained as a result, and by realizing production dispatching cooperative scheduling in job scheduling to short machine of corresponding Direct Distribution time, it realizes the reasonable utilization of dispatching resource, improves customer satisfaction with services.
Description
Technical field
The present invention relates to enterprise's production and operation administrative skill fields more particularly to a kind of Direct Distribution Time Dependent in machine
The parallel machine dispatching method in geographical location.
Background technique
In recent years, the rapid development with extensive use of internet the relevant technologies change the every aspect of society deeply.It passes
In manufacturing industry of uniting, with popularizing for Internet technology, manufacturing enterprise can realize that idle manufacturing recourses are total by internet platform
It enjoys, remote enterprise client can obtain slack resources related data by internet in real time and realize transaction.Due to idle manufacture
Resource distribution is in different geographical locations, and thus the different location production dispatching cooperative scheduling problem of bring manufacturing recourses is to production scheduling
New challenge is researched and proposed.For example, an enterprise positioned at the ground A finds have positioned at B and C two places system by internet hunt
Enterprise order can be completed by making quotient, and due to the geographical location B with C difference, under the premise of using identical means of transportation, order is completed
Distribution time afterwards is different and depends on the geographical location of B and C.
Therefore the scheduling problem can be abstracted as to following Direct Distribution Time Dependent in the parallel processor scheduling of machine:
There is the identical machine M of m platform working ability1,M2,......,MmAnd assume that the processing speed of machine is 1；N mutually solely
Vertical operation J1,J2,......,Jn, operation JjArrival time be rj, rjFor positive number, and operation cannot open before this time
Begin to process, process time pj, the Direct Distribution time dependent on processing machine isThe completion date of operation is expressed as Cj,
The service span of operation is expressed as Sj, service span and refer to that operation undergoes Direct Distribution to reach client after processing is completed on machine
There is operation J in the time at placejScheduling is in machine MiOn, then operation JjService spanEvery machine is in same a period of time
Quarter can only process an operation, and process can not interrupt.The target of scheduling is to minimize service span summation.Reference
Grahametal.(Graham R L,Lawler E L,Lenstra J K,et al.Optimization and
approximation in deterministic sequencing and scheduling:a Survey[J].Annals
Of Discrete Mathematics, 1979,5 (1): 287-326) propose three parameter alphas | β | γ representation, this problem are usual
It is expressed asHere PmIndicate the scheduling type of m parallel machine, | rjIndicate the time that operation reaches,It indicates
Dependent on the Direct Distribution time of machine, | ∑ SjIndicate service span and.Problem is strong NP-hard problem,
Because even being simplest single machine situation 1 | rj|∑CjProblem be all strong NP-hard problem (referring specifically to Lenstra J K,
Rinnooy Kan A H G,Brucker P.Complexity of machine scheduling problems[J]
.Annals of Discrete Machines,1977,1(4):343-362)。
Currently, correlative study of the internet in conjunction with operation management receives the concern of domestic and foreign scholars, but most researchs
Achievement concentrates on manufacture in operation and supply chain management, three buying, logistics key areas, and considers the production under interconnection background
Scheduling problem research achievement is less.
Parallel processor scheduling is introduced since McNaughton will minimize completion date and target in nineteen fifty-nine, is had studied
(referring specifically to Mcnaughton R.Scheduling with deadlines and after the parallel machine problem that number of machines is m
Loss functions.Management Science, 1959,6:1-12), many scholars have carried out problems deep
Research.Since minimum completion date and problem are to minimize the special case of Total weighted completion time problem, weighting is minimized
The related conclusions of completion date and problem are also applied for corresponding minimum completion date and problem.Also researcher adjusts in tradition
Machine is added in degree problem using factors such as constraint, study efficacy, totle drilling cost constraints, and has carried out on this basis a series of
Research work.
Current many scholars are studied with regard to parallel processor scheduling, though achieving certain achievement, only lack portion
Scholar is divided to consider that operation has this situation of Direct Distribution time.It is straight that Li Kai et al. has studied the production-inventory-in two-echelon supply-chain
Dispatching cooperative scheduling problem is connect, the CTA-TS algorithm of Solve problems is proposed and demonstrates the validity of algorithm (referring specifically to Lee
Triumphant, Zhou Chao, Ma Ying consider single machine JIT scheduling problem [J] the Operations research and mamagement science of release time, 2016,25 (3)).Li et al. people
The shared scheduling problem of Distributed Manufacturing Resources is studied, operation has the Direct Distribution time, and two kinds of heuritic approaches of researching and designing are come
Solving regulation goal is minimizes Maximal Makespan and problem (referring specifically to Li K, Zhou T, Liu B H, et al.A
multi-agent system for sharing distributed manufacturing resources[J].Expert
Systems with Applications,2018,99:32-43.)。
Since under traditional distribution mode, manufacturing recourses are in same position, the studies above commonly assumes that the straight of each operation
Connecing distribution time is unique value.And under " internet+" environment, consider this premise of manufacture resource sharing, operation is directly matched
Send Time Dependent in machine location, there is changeability, thus conventional scheduling method be not using.Based on this, the present invention is proposed
A kind of Direct Distribution Time Dependent is in the parallel machine dispatching method in machine geographical location.
Summary of the invention
The purpose of the present invention is to solve existing dispatching methods not to consider that the Direct Distribution time has asking for changeability
Topic, and a kind of Direct Distribution Time Dependent proposed is in the parallel machine dispatching method in machine geographical location.
In order to achieve the above object, the present invention is achieved by the following technical programs:
A kind of Direct Distribution Time Dependent is in the parallel machine dispatching method in machine geographical location, comprising the following steps:
Step 1, initialization: generating initial solution with MEST algorithm, obtains initial solution π, and corresponding target function value is ∑ S
(π), enabling current optimal solution is π*=π, ∑ S (π)*=∑ S (π), wherein π be scheduling scheme, ∑ S (π) be service span and；
Step 2, setting initial temperature T=100 ∑ S (π)*, minimum temperature ε=0.0001, cooling rate α=0.95；
If step 3, T≤ε return to optimal solution π*And optimal value ∑ S (π)*, exit；
The number of iterations L=n under step 4, setting unified temperature2/3；
Step 5 generates random number x1(x1~[0,1]), if x1> 0.9 goes to step 7；
Step 6, crossover operation: one new σ (σ ∈ N of selection2(π)), calculating target function value ∑ S (σ) goes to step 8；
Step 7, insertion operation: one new σ (σ ∈ N of selection1(π)), calculating target function value ∑ S (σ)；
Step 8, Δ S=∑ S (σ)-∑ S (π) go to step 10 such as Δ S < 0；
Step 9 generates random number x2(x2~[0,1]), if exp (- Δ U/T)≤x2Go to step 11；
Step 10 receives new explanation: π=σ；∑ S (π)=∑ S (σ), if ∑ S (π) < ∑ S (σ)*, then π*=π, ∑ S (π)*
=∑ S (π)；
Step 11, L=L-1 go to step 5 if L > 0, and otherwise T=α T, goes to step 3.
Preferably, the MEST algorithm specifically includes the following steps:
S1, given operation set J, to any machine Mi,ni=0, Ci=0, Sj=0, a=0, whereinFor the scheduling collection of machine i, Ci=0 is the completion date of machine i, Sj=0 is put into service span for operation j；
S2, for any operation J in operation set Jj, calculate operation j process time and the Direct Distribution time and, i.e.,If it is corresponding to exist simultaneously multiple machinesThen select label most
Small machine, by operation JjIt is added to machine MkOperation set in, i.e. Jj∈Jk, by job schedulings all in operation set J to phase
It answers on machine；
S3, a=a+1 is enabled, to the operation set J being dispatched on machine aaIt is scheduled；
S4, judge operation set JaIn whether have the operation that arrived, if release time be less than current machine completion date,
That is rj≤Ca, then operation arrived, and will arrived the shortest operation J of process time in operationjIt is added to machine MaCurrent son scheduling
πaFinally, shortest operation of multiple process times if it exists, then preferentially processing arrival time small operation, if not arrived
Operation then arranges rjSuch as there are multiple r in the smallest operationjMinimum then arranges the smallest operation of label, i.e.,πa=(Jj)||πa, na=na+ 1, Ca=Ca+pj,
S5、Ja=Ja\{Jj, Ja≠ φ, then turn S4；Otherwise, turn S6；
If S6, a=m, output π andOtherwise, turn S3.
Preferably, the runing time of the MEST algorithm is O (mn2)。
Advantage is compared with prior art:
1, the present invention is under current social production background, and research operation Direct Distribution Time Dependent is in machine geography position
The parallel processor scheduling set realizes effectively integrating and efficiently utilizing for widely distributed manufacturing recourses by dispatching algorithm, and
Technical support is provided to the realization of current Chinese societyization manufacture, when solving existing dispatching method and not considering Direct Distribution
Between there is the problem of changeability.
2, the solution that the present invention is obtained using MEST algorithm is as initial solution, in conjunction with exchange transformation and insertion transformation to change son
Number of jobs in scheduling, and (arrive first and first process) rule by SPT (short job priority) and ERT and realize production scheduling sequence,
Obtain satisfied production scheduling as a result, and by job scheduling to short machine of corresponding Direct Distribution time, realize production dispatching
Cooperative scheduling realizes the reasonable utilization of dispatching resource；The present invention dispenses cooperative scheduling mode by production, realizes manufacturing recourses
With the efficient utilization of dispatching resource, customer satisfaction with services is improved.
3, the experiment proved that, MEST algorithm is substantially better than EST algorithm, and parallel machine dispatching method proposed by the present invention can
Optimize the solution of MEST algorithm
Specific embodiment
Combined with specific embodiments below the present invention is made further to explain.
Embodiment
A kind of Direct Distribution Time Dependent proposed by the present invention in the parallel machine dispatching method in machine geographical location, including with
Lower step:
Step 1, initialization: generating initial solution with MEST algorithm, obtains initial solution π, and corresponding target function value is ∑ S
(π), enabling current optimal solution is π*=π, ∑ S (π)*=∑ S (π), wherein π be scheduling scheme, ∑ S (π) be service span and；
Step 2, setting initial temperature T=100 ∑ S (π)*, minimum temperature ε=0.0001, cooling rate α=0.95；
If step 3, T≤ε return to optimal solution π*And optimal value ∑ S (π)*, exit；
The number of iterations L=n under step 4, setting unified temperature2/3；
Step 5 generates random number x1(x1~[0,1]), if x1> 0.9 goes to step 7；
Step 6, crossover operation: one new σ (σ ∈ N of selection2(π)), calculating target function value ∑ S (σ) goes to step 8；
Step 7, insertion operation: one new σ (σ ∈ N of selection1(π)), calculating target function value ∑ S (σ)；
Step 8, Δ S=∑ S (σ)-∑ S (π) go to step 10 such as Δ S < 0；
Step 9 generates random number x2(x2~[0,1]), if exp (- Δ U/T)≤x2Go to step 11；
Step 10 receives new explanation: π=σ；∑ S (π)=∑ S (σ), if ∑ S (π) < ∑ S (σ)*, then π*=π, ∑ S (π)*
=∑ S (π)；
Step 11, L=L-1 go to step 5 if L > 0, and otherwise T=α T, goes to step 3.
In the present invention, MEST algorithm specifically includes the following steps:
S1, given operation set J, to any machine Mi,ni=0, Ci=0, Sj=0, a=0, whereinFor the scheduling collection of machine i, Ci=0 is the completion date of machine i, Sj=0 is put into service span for operation j；
S2, for any operation J in operation set Jj, calculate operation j process time and the Direct Distribution time and, i.e.,If it is corresponding to exist simultaneously multiple machinesThen select label most
Small machine, by operation JjIt is added to machine MkOperation set in, i.e. Jj∈Jk, by job schedulings all in operation set J to phase
It answers on machine；
S3, a=a+1 is enabled, to the operation set J being dispatched on machine aaIt is scheduled；
S4, judge operation set JaIn whether have the operation that arrived, if release time be less than current machine completion date,
That is rj≤Ca, then operation arrived, and will arrived the shortest operation J of process time in operationjIt is added to machine MaCurrent son scheduling
πaFinally, shortest operation of multiple process times if it exists, then preferentially processing arrival time small operation, if not arrived
Operation then arranges rjSuch as there are multiple r in the smallest operationjMinimum then arranges the smallest operation of label, i.e.,πa=(Jj)||πa, na=na+ 1, Ca=Ca+pj,
S5、Ja=Ja\{Jj, Ja≠ φ, then turn S4；Otherwise, turn S6；
If S6, a=m, output π andOtherwise, turn S3；
The runing time of MEST algorithm is O (mn2)。
We are distinguished using the parallel machine dispatching method that traditional EST algorithm, MEST algorithm and the embodiment of the present invention propose
To 2,4,6,8,10 machines, 30,50,100,200 operationsProblem is solved, and experimental result is shown in Table 1
With table 2.
Wherein the parallel machine dispatching method of EST algorithm, MEST algorithm and proposition of the embodiment of the present invention is realized by Java, and
It is encoded in Myeclipse 10, experimental situation is CPU-Intel (R) (TM) i3 3.10GHz, memory -2.00GB, operates system
System-Microsoft Windows7.
Wherein, EST algorithm specifically includes the following steps:
Step1. it initializes: given operation set J, to any machine Mi,ni=0, Ci=0, Sj=0；
Step2.If it is corresponding to exist simultaneously multiple machinesThen select label minimum
Machine；
Step3. building can and operation set Ja, judge in current work collection J each operation whether can and, ifThen operation can and, then operation Jj∈Ja；
If Step4. Ja≠ φ then turns Step5, and arrival time the smallest operation J is otherwise selected from operation set JjIf together
When there are multiple operation arrival times are minimum, then select wherein process time shortest operation, Jj∈Ja, turn Step6；
Step5. from operation set JaMiddle selection process time shortest operation JjIt is arranged into machine MkOn processed, i.e.,
Step6. by operation JjIt is added to machine MkCurrent son scheduling πkFinally, i.e.πk=(Jj)
||πk, nk=nk+ 1, Ck=Ck+pj,
Step7.J=J { Jj}；
Step8.J ≠ φ then turns Step2；Otherwise, output π and
Wherein operation arrival time, process time and Direct Distribution time generate at random, operation arrival time and processing
Time value range is 0~30, and the value range of Direct Distribution time is 0~30 and 0~100.In order to ensure the result of experiment
More objective, we have done 100 groups of experiments at random respectively, and take the average value of calculated result service span sum.We are indicated with *
In 100 random experiments for accordingly calculating situation, the average value which obtains objective function is best in 3 algorithms.It is fixed
The corresponding Gap value of adopted algorithm MEST indicates that algorithm MEST improves the percentage of EST algorithm performance, and provides as given a definition:Wherein fESTAnd fMESTRespectively indicate the target function value that EST algorithm and MEST algorithm calculate.
Table 1: the experimental result that Direct Distribution time value is 0~30
In table 1, m indicates machine number of units in experiment；N indicates number of jobs.
Table 2: the experimental result that Direct Distribution time value is 0~100
In table 2, m indicates machine number of units in experiment；N indicates number of jobs.
Above-mentioned Tables 1 and 2 the results showed that the performance of MEST algorithm is generally better than EST algorithm, the present invention is implemented
The parallel machine dispatching method of example has a degree of improvement to act on MEST algorithm.In all experiments, EST algorithm is only capable of in machine
Optimal solution is obtained in the case that number is less, it is optimal by the parallel machine dispatching method acquisition of the embodiment of the present invention under remaining situation
Solution.In 40 groups of tests MEST algorithm to the improvement performance of EST algorithm between 0.45%~39.70%, the embodiment of the present invention
Parallel machine dispatching method is to the improvement performance of EST algorithm between 0.58%~39.71%.
The experimental result in Tables 1 and 2 is compared, since MEST algorithm is paid the utmost attention to job scheduling to corresponding Direct Distribution
Time the smallest machine, in the case of the Direct Distribution time is larger, the MEST algorithm performance modified to EST algorithm, which has, obviously to be mentioned
It rises.The modification performance of MEST algorithm is between 0.45%~7.67% in table 1, and the modification performance of MEST algorithm exists in table 2
Between 3.69%~39.70%.All experiments of table 1, compared with EST algorithm, the parallel machine dispatching method of the embodiment of the present invention is flat
2.32% is improved, all experiments of table 2, compared with EST algorithm, the parallel machine dispatching method of the embodiment of the present invention is averagely improved
18.62%.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Anyone skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (3)
1. a kind of Direct Distribution Time Dependent is in the parallel machine dispatching method in machine geographical location, which is characterized in that including following
Step:
Step 1, initialization: generating initial solution with MEST algorithm, obtains initial solution π, and corresponding target function value is ∑ S (π), enables
Current optimal solution is π*=π, ∑ S (π)*=∑ S (π), wherein π be scheduling scheme, ∑ S (π) be service span and；
Step 2, setting initial temperature T=100 ∑ S (π)*, minimum temperature ε=0.0001, cooling rate α=0.95；
If step 3, T≤ε return to optimal solution π*And optimal value ∑ S (π)*, exit；
The number of iterations L=n under step 4, setting unified temperature2/3；
Step 5 generates random number x1(x1~[0,1]), if x1> 0.9 goes to step 7；
Step 6, crossover operation: one new σ (σ ∈ N of selection2(π)), calculating target function value ∑ S (σ) goes to step 8；
Step 7, insertion operation: one new σ (σ ∈ N of selection1(π)), calculating target function value ∑ S (σ)；
Step 8, Δ S=∑ S (σ)-∑ S (π) go to step 10 such as Δ S < 0；
Step 9 generates random number x2(x2~[0,1]), if exp (- Δ U/T)≤x2Go to step 11；
Step 10 receives new explanation: π=σ；∑ S (π)=∑ S (σ), if ∑ S (π) < ∑ S (σ)*, then π*=π, ∑ S (π)*=
∑S(π)；
Step 11, L=L-1 go to step 5 if L > 0, and otherwise T=α T, goes to step 3.
2. a kind of Direct Distribution Time Dependent according to claim 1 is in the parallel machine dispatching method in machine geographical location,
It is characterized in that, the MEST algorithm specifically includes the following steps:
S1, given operation set J, to any machine Mi,ni=0, Ci=0, Sj=0, a=0, whereinFor machine
The scheduling collection of device i, Ci=0 is the completion date of machine i, Sj=0 is put into service span for operation j；
S2, for any operation J in operation set Jj, calculate operation j process time and the Direct Distribution time and, i.e.,If it is corresponding to exist simultaneously multiple machinesThen select label most
Small machine, by operation JjIt is added to machine MkOperation set in, i.e. Jj∈Jk, by job schedulings all in operation set J to phase
It answers on machine；
S3, a=a+1 is enabled, to the operation set J being dispatched on machine aaIt is scheduled；
S4, judge operation set JaIn whether have the operation that arrived, if release time be less than current machine completion date, i.e. rj
≤Ca, then operation arrived, and will arrived the shortest operation J of process time in operationjIt is added to machine MaCurrent son scheduling πaMost
Afterwards, shortest operation of multiple process times if it exists, then preferentially processing arrival time small operation, if the operation that not arrived
Then arrange rjSuch as there are multiple r in the smallest operationjMinimum then arranges the smallest operation of label, i.e.,
πa=(Jj)||πa, na=na+ 1, Ca=Ca+pj,
S5、Ja=Ja\{Jj, Ja≠ φ, then turn S4；Otherwise, turn S6；
If S6, a=m, output π andOtherwise, turn S3.
3. a kind of Direct Distribution Time Dependent according to claim 1 or 2 is in the parallel machine dispatching party in machine geographical location
Method, which is characterized in that the runing time of the MEST algorithm is O (mn2)。
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