CN104391488A - Optimizing and dispatching method of energy consumption of flexible flow shop with associated adjustment time and sequence - Google Patents
Optimizing and dispatching method of energy consumption of flexible flow shop with associated adjustment time and sequence Download PDFInfo
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- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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Abstract
The invention discloses an optimizing and dispatching method of energy consumption of a flexible flow shop with associated adjustment and sequence. The method comprises the following steps: S1, searching on the dispatching problem of the flexible flow shop having adjustment time associated with sequence, wherein the adjustment time is defined into one associated with workpiece sequence and the other one associated with workpiece sequence and machines; S2, establishing the following mathematic models; S3, using the minimum overall energy consumption as a target and providing three heuristics algorithms with respect to a problem existing in the problems resolved with an NEH algorithm; S4, verifying the above three algorithms, providing two lower bounds of the problem and designing one simulation experiment based on a split block experiment; S5, analyzing factors, algorithms, lower bounds and CPU operational time according to the simulation results. According to the optimizing and dispatching method of energy consumption of the flexible flow shop with associated adjustment and sequence, the energy consumption is optimized and the cost is saved.
Description
Technical field
The present invention relates to flexible Flow Shop energy optimization dispatching method, particularly relate to the flexible Flow Shop energy optimization dispatching method that a kind of regulation time is relevant to order.
Background technology
Classical flexible Flow Shop scheduling (FFS) (or hybrid flow shop scheduling (HFS)) problem has had a large amount of achievements in research.This problem has following characteristics: each workpiece must successively through a series of machine group processing be made up of parallel machine; All workpiece are ready at all times to start processing zero; Regulation time is uncorrelated with workpiece order and inside the process time being included in workpiece.
Classical FFS scheduling problem has done larger simplification to practical problems, and in actual production environment, dispatch environment wants complexity many, and for the needs of theoretical research and engineering reality, researcher proposes various FFS scheduling problem model and studies.Most achievement in research is to optimize production efficiency index for target before, such as, minimizes Maximal Makespan, total complete time, total delay time etc.But production efficiency might not be unique factor that supvr thinks.In recent years, because a series of serious environmental impact and energy cost rise, production energy-saving was made more and more to receive the concern of people.
Summary of the invention
Object of the present invention provides the flexible Flow Shop energy optimization dispatching method that a kind of regulation time is relevant to order, optimizes energy consumption, has saved cost.
For achieving the above object, the present invention adopts following technical scheme:
The flexible Flow Shop energy optimization dispatching method that regulation time is relevant to order, comprises the steps:
S1, to study to the relevant flexible Flow Shop Scheduling of order for regulation time, wherein regulation time is defined as two classes: a class is relevant to workpiece order, another kind of relevant with machine to workpiece order;
S2, founding mathematical models are as follows:
j= 1, 2,…,
n, , (1)
Constraint condition:
j=1,2 ...,
n,
s=1,2,
k, (2)
j= 1, 2,…,
n, (3)
j= 1, 2,…,
n,
s= 1,2,…
k ,
(4)
i= 1, 2,…,
n,
j= 1, 2,…,
n,
h= 1,2,…,
m s ,
s= 1,2,…
k, (5)
i,
jQ hs , (6)
j= 1, 2,…,
n,
h= 1,2,…,
m s ,
s= 1,2,…
k, (7)
h= 1,2,…,
m s ,
s= 1,2,…
k,,
jQ hs , (8)
i=
j, (9)
And substantially meet:
npiece count
knumber of stages
r j the release time of workpiece
, j=1,2 ...,
n
m s the machine quantity of stage s,
s=1,2 ...,
k
p jhs the process time of workpiece j on the machine h in s stage
, h=1,2 ...,
m s
b js workpiece j opens process time in the s stage
c js workpiece j completed between man-hour in the s stage
sT 1 the stage collection that regulation time is relevant to order
sT 2 regulation time and workpiece order and workpiece be arranged into the relevant stage collection of machine
q hs be arranged in the workpiece collection that the machine h of stage s processes
In above-mentioned expression formula: the objective function of formula (1) problem of representation, minimized total energy cost, total energy consumption three part forms: operation energy consumption cost (i.e. the Part I of formula (1)), standby energy consumption (i.e. the Part II of formula (1)) and pre-thermal energy consumption (i.e. the Part III of formula (1)); Formula (2) represents each workpiece needs successively through the processing in s stage, namely each workpiece it on last stage undressed complete before, the processing in the current generation can not be started; Formula (3) represents that workpiece process time can not early than the release time of this workpiece in this stage in the beginning in current stage; Formula (4) represents that each workpiece can only be arranged on a machine at one time and processes; Formula (5) represents that machine can only process a workpiece at one time.If represent that the beginning of workpiece j on stage s machine h is greater than the completion date of workpiece i process time, this meaning workpiece i, j is arranged in that the machine h of stage s is upper to be processed continuously.If then formula (5) perseverance is set up, and wherein M represents an enough large number; Formula (6) calculates workpiece at the completion date in per stage, and its completion date equals workpiece and to add the process time of workpiece on this stage machine and regulation time process time in the beginning in this stage.Owing to contemplated by the invention the two classes regulation time relevant to order, therefore when the current generation belongs to first kind regulation time, workpiece has formula (6) first expression formulas to calculate in the completion in per stage, otherwise workpiece is calculated by formula (6) second expression formulas at the completion date in per stage; Formula (7) defines workpiece and opens process time in per stage, and its value equals the higher value of workpiece between the started process time that completion date on last stage and workpiece are arranged in machine.When
s=1, and
j=1; Formula (8) determine at one's leisure between the state (holding state or machine are from shutting down to the preheat mode of starting shooting) of section inner machine.Formula (8) first is expressed and is defined the quantity that machine exists free time section.If meet formula (8) second and the 3rd expression formula, then machine this free time section be in preheat mode.Otherwise machine is in holding state.Formula (9) represents the span of decision variable;
S3, with minimized total energy consumption for target, for employing NEH such problem of Algorithm for Solving time Problems existing, propose three kinds of heuritic approaches; The first algorithm (EPRA) is based on the processing queue of the energy consumption cost acquisition workpiece of work pieces process time; Second algorithm (ESRA) is based on the job sequence of the energy consumption cost acquisition workpiece of workpiece regulation time; 3rd algorithm (ESPRA), in conjunction with the advantage of EPRA and ESRA algorithm, builds virtual workpiece by ESRA algorithm, and EPRA algorithm obtains the processing sequence of virtual workpiece;
S4, above-mentioned three kinds of algorithms to be verified, propose two lower bounds of this problem, devise a l-G simulation test based on split plot experiment;
S5, by carrying out factor analysis to simulation result, Algorithm Analysis, lower bound analysis and CPU analyze working time, and analysis result shows: all principal elements reveal appreciable impact to object table except algorithm factor; ESPRA Algorithm for Solving effect is best in these three kinds of algorithms; LB1 is better than LB2; The working time of ESPRA algorithm is significantly smaller than other two kinds of algorithms.
Further, described NEH algorithm comprises the steps:
Step 1: sort according to the decreasing order that workpiece is always processed, obtains work pieces process queue S;
Step 2: according to processing queue S, gets its first two workpiece and carries out scheduling and obtain optimal scheduling;
Step 3: read next workpiece according to processing queue S, is inserted into this workpiece certain position in the workpiece arrangement of having dispatched, makes regulation index minimum;
Step 4: repeat said process, until all workpiece in processing queue are all dispatched complete;
Further, described ESRA algorithm comprises the steps:
Step 1: build energy consumption matrix ESST.The energy consumption free time cost total according to ESST matrix computations workpiece also sorts to workpiece according to its ascending order, obtains work pieces process order S;
Step 2: read the first two workpiece in processing queue S and carry out optimal scheduling according to objective function, obtaining partial scheduling result OP.Workpiece is deleted from queue S;
Step 3: from O=3 to n, reads processing queue S o workpiece, then workpiece o is inserted into o possible position in OP, finally selects optimum local scheduling scheme as the processing queue of workpiece
oP * ;
Step 4: according to processing queue OP * and EST rule, arranges workpiece to process on every platform machine in each stage.
Further, described ESPRA algorithm comprises the steps:
Step 1: initialization local scheduling scheme calculates OP*=0;
Step 2: build ESST matrix;
Step 3: according to ESST matrix, workpiece sorts according to the total idle energy consumption cost ascending order based on regulation time, obtains work pieces process queue S;
Step 4: according to processing queue S, builds virtual workpiece collection, calculates the process time of each virtual workpiece;
Step 5: decreasing order process time according to virtual workpiece sorts to virtual workpiece, obtains the processing queue σ of virtual workpiece;
Step 6: read two virtual workpieces before σ, process to the machine in per stage according to EST regulation arrangement workpiece, the scheduling scheme assignment of minimum energy consumption cost to OP*, and this virtual workpiece is deleted from σ;
Step 7: consider the next virtual workpiece in σ;
Step 8: virtual workpiece to be inserted in OP* all possible position and to find energy consumption cost that scheduling scheme minimum, assignment to OP *, and this virtual workpiece being deleted from σ;
Step 9: if walk 10 steps, otherwise forward step 7 to;
Step 10: the total energy consumption cost returned.
Compared with prior art, the flexible Flow Shop energy optimization dispatching method that a kind of regulation time of the present invention is relevant to order, optimizes energy consumption, has saved cost.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
The flexible Flow Shop energy optimization dispatching method that regulation time is relevant to order, comprises the steps:
S1, to study to the relevant flexible Flow Shop Scheduling of order for regulation time, wherein regulation time is defined as two classes: a class is relevant to workpiece order, another kind of relevant with machine to workpiece order;
The present invention is directed to and there are two kinds of regulation time dispatch to the relevant flexible Flow Shop of order and be studied.Such problem is defined as follows.Have n workpiece or task, each workpiece is wanted successively through the processing in K stage.Each stage by MS(S=1,2 ..., K) and the parallel composition of platform non-equally.Every platform machine has Three models: run, standby and stopping.Correspond to the Three models of every platform machine, the energy consumption of every platform machine is made up of three parts: operation energy consumption, idle energy consumption and pre-thermal energy consumption.The machine of each workpiece needs in per stage.Workpiece be not the same time arrive, each workpiece have one time of arrival rj.On uniform machinery, two workpiece of Continuous maching also exist regulation time.An important feature is herein: the regulation time of workpiece on some stage is only relevant to workpiece order, and not only depends on the order of work at its regulation time of some other stage, and relevant to the machine assigned by workpiece.
S2, founding mathematical models are as follows:
j= 1, 2,…,
n, , (1)
Constraint condition:
j=1,2 ...,
n,
s=1,2,
k, (2)
j= 1, 2,…,
n, (3)
j= 1, 2,…,
n,
s= 1,2,…
k ,
(4)
i= 1, 2,…,
n,
j= 1, 2,…,
n,
h= 1,2,…,
m s ,
s= 1,2,…
k,(5)
i,
jQ hs , (6)
j= 1, 2,…,
n,
h= 1,2,…,
m s ,
s= 1,2,…
k, (7)
h= 1,2,…,
m s ,
s= 1,2,…
k,,
jQ hs , (8)
i=
j, (9)
And substantially meet:
npiece count
knumber of stages
r j the release time of workpiece
, j=1,2 ...,
n
m s the machine quantity of stage s,
s=1,2 ...,
k
p jhs the process time of workpiece j on the machine h in s stage
, h=1,2 ...,
m s
b js workpiece j opens process time in the s stage
c js workpiece j completed between man-hour in the s stage
sT 1 the stage collection that regulation time is relevant to order
sT 2 regulation time and workpiece order and workpiece be arranged into the relevant stage collection of machine
q hs be arranged in the workpiece collection that the machine h of stage s processes
In above-mentioned expression formula: the objective function of formula (1) problem of representation, minimized total energy cost, total energy consumption three part forms: operation energy consumption cost (i.e. the Part I of formula (1)), standby energy consumption (i.e. the Part II of formula (1)) and pre-thermal energy consumption (i.e. the Part III of formula (1)); Formula (2) represents each workpiece needs successively through the processing in s stage, namely each workpiece it on last stage undressed complete before, the processing in the current generation can not be started; Formula (3) represents that workpiece process time can not early than the release time of this workpiece in this stage in the beginning in current stage; Formula (4) represents that each workpiece can only be arranged on a machine at one time and processes; Formula (5) represents that machine can only process a workpiece at one time.If represent that the beginning of workpiece j on stage s machine h is greater than the completion date of workpiece i process time, this meaning workpiece i, j is arranged in that the machine h of stage s is upper to be processed continuously.If then formula (5) perseverance is set up, and wherein M represents an enough large number; Formula (6) calculates workpiece at the completion date in per stage, and its completion date equals workpiece and to add the process time of workpiece on this stage machine and regulation time process time in the beginning in this stage.Owing to contemplated by the invention the two classes regulation time relevant to order, therefore when the current generation belongs to first kind regulation time, workpiece has formula (6) first expression formulas to calculate in the completion in per stage, otherwise workpiece is calculated by formula (6) second expression formulas at the completion date in per stage; Formula (7) defines workpiece and opens process time in per stage, and its value equals the higher value of workpiece between the started process time that completion date on last stage and workpiece are arranged in machine.When
s=1, and
j=1; Formula (8) determine at one's leisure between the state (holding state or machine are from shutting down to the preheat mode of starting shooting) of section inner machine.Formula (8) first is expressed and is defined the quantity that machine exists free time section.If meet formula (8) second and the 3rd expression formula, then machine this free time section be in preheat mode.Otherwise machine is in holding state.Formula (9) represents the span of decision variable;
S3, with minimized total energy consumption for target, for employing NEH such problem of Algorithm for Solving time Problems existing, propose three kinds of heuritic approaches; The first algorithm (EPRA) is based on the processing queue of the energy consumption cost acquisition workpiece of work pieces process time; Second algorithm (ESRA) is based on the job sequence of the energy consumption cost acquisition workpiece of workpiece regulation time; 3rd algorithm (ESPRA), in conjunction with the advantage of EPRA and ESRA algorithm, builds virtual workpiece by ESRA algorithm, and EPRA algorithm obtains the processing sequence of virtual workpiece;
Described NEH algorithm comprises the steps:
Step 1: sort according to the decreasing order that workpiece is always processed, obtains work pieces process queue S;
Step 2: according to processing queue S, gets its first two workpiece and carries out scheduling and obtain optimal scheduling;
Step 3: read next workpiece according to processing queue S, is inserted into this workpiece certain position in the workpiece arrangement of having dispatched, makes regulation index minimum;
Step 4: repeat said process, until all workpiece in processing queue are all dispatched complete.
Described ESRA algorithm comprises the steps:
Step 1: build energy consumption matrix ESST.The energy consumption free time cost total according to ESST matrix computations workpiece also sorts to workpiece according to its ascending order, obtains work pieces process order S;
Step 2: read the first two workpiece in processing queue S and carry out optimal scheduling according to objective function, obtaining partial scheduling result OP.Workpiece is deleted from queue S;
Step 3: from O=3 to n, reads processing queue S o workpiece, then workpiece o is inserted into o possible position in OP, finally selects optimum local scheduling scheme as the processing queue of workpiece
oP * ;
Step 4: according to processing queue OP * and EST rule, arranges workpiece to process on every platform machine in each stage;
Described ESPRA algorithm comprises the steps:
Step 1: initialization local scheduling scheme calculates OP*=0;
Step 2: build ESST matrix;
Step 3: according to ESST matrix, workpiece sorts according to the total idle energy consumption cost ascending order based on regulation time, obtains work pieces process queue S;
Step 4: according to processing queue S, builds virtual workpiece collection, calculates the process time of each virtual workpiece;
Step 5: decreasing order process time according to virtual workpiece sorts to virtual workpiece, obtains the processing queue σ of virtual workpiece;
Step 6: read two virtual workpieces before σ, process to the machine in per stage according to EST regulation arrangement workpiece, the scheduling scheme assignment of minimum energy consumption cost to OP*, and this virtual workpiece is deleted from σ;
Step 7: consider the next virtual workpiece in σ;
Step 8: virtual workpiece to be inserted in OP* all possible position and to find energy consumption cost that scheduling scheme minimum, assignment to OP *, and this virtual workpiece being deleted from σ;
Step 9: if walk 10 steps, otherwise forward step 7 to;
Step 10: the total energy consumption cost returned.
S4, above-mentioned three kinds of algorithms to be verified, propose two lower bounds of this problem, devise a l-G simulation test based on split plot experiment;
S5, by carrying out factor analysis to simulation result, Algorithm Analysis, lower bound analysis and CPU analyze working time, and analysis result shows: all principal elements reveal appreciable impact to object table except algorithm factor; ESPRA Algorithm for Solving effect is best in these three kinds of algorithms; LB1 is better than LB2; The working time of ESPRA algorithm is significantly smaller than other two kinds of algorithms.
The flexible Flow Shop energy optimization dispatching method that a kind of regulation time of the present invention is relevant to order, optimizes energy consumption, has saved cost.
The above is the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications are also considered as protection scope of the present invention.
Claims (4)
1. the flexible Flow Shop energy optimization dispatching method that regulation time is relevant to order, is characterized in that, comprise the steps:
S1, to study to the relevant flexible Flow Shop Scheduling of order for regulation time, wherein regulation time is defined as two classes: a class is relevant to workpiece order, another kind of relevant with machine to workpiece order;
S2, founding mathematical models are as follows:
j= 1, 2,…,
n, , (1)
Constraint condition:
j=1,2 ...,
n,
s=1,2,
k, (2)
j= 1, 2,…,
n, (3)
j= 1, 2,…,
n,
s= 1,2,…
k ,
(4)
i= 1, 2,…,
n,
j= 1, 2,…,
n,
h= 1,2,…,
m s ,
s= 1,2,…
k,(5)
i,
jQ hs , (6)
j= 1, 2,…,
n,
h= 1,2,…,
m s ,
s= 1,2,…
k, (7)
h= 1,2,…,
m s ,
s= 1,2,…
k,,
jQ hs , (8)
i=
j, (9)
And substantially meet:
npiece count
knumber of stages
r j the release time of workpiece
, j=1,2 ...,
n
m s the machine quantity of stage s,
s=1,2 ...,
k
p jhs the process time of workpiece j on the machine h in s stage
, h=1,2 ...,
m s
b js workpiece j opens process time in the s stage
c js workpiece j completed between man-hour in the s stage
sT 1 the stage collection that regulation time is relevant to order
sT 2 regulation time and workpiece order and workpiece be arranged into the relevant stage collection of machine
q hs
be arranged in the workpiece collection that the machine h of stage s processes
In above-mentioned expression formula: the objective function of formula (1) problem of representation, minimized total energy cost, total energy consumption three part forms: operation energy consumption cost (i.e. the Part I of formula (1)), standby energy consumption (i.e. the Part II of formula (1)) and pre-thermal energy consumption; Formula (2) represents each workpiece needs successively through the processing in s stage, namely each workpiece it on last stage undressed complete before, the processing in the current generation can not be started; Formula (3) represents that workpiece process time can not early than the release time of this workpiece in this stage in the beginning in current stage; Formula (4) represents that each workpiece can only be arranged on a machine at one time and processes; Formula (5) represents that machine can only process a workpiece at one time;
owing to contemplated by the invention the two classes regulation time relevant to order, therefore when the current generation belongs to first kind regulation time, workpiece has formula (6) first expression formulas to calculate in the completion in per stage, otherwise workpiece is calculated by formula (6) second expression formulas at the completion date in per stage; Formula (7) defines workpiece and opens process time in per stage, and its value equals the higher value of workpiece between the started process time that completion date on last stage and workpiece are arranged in machine;
When
s=1, and
j=1; Formula (8) determine at one's leisure between the state (holding state or machine are from shutting down to the preheat mode of starting shooting) of section inner machine, formula (8) first is expressed and is defined the quantity that machine exists free time section, if meet formula (8) second and the 3rd expression formula, then machine this free time section be in preheat mode, otherwise machine is in holding state, formula (9) represents the span of decision variable;
S3, with minimized total energy consumption for target, for employing NEH such problem of Algorithm for Solving time Problems existing, propose three kinds of heuritic approaches; The first algorithm (EPRA) is based on the processing queue of the energy consumption cost acquisition workpiece of work pieces process time; Second algorithm (ESRA) is based on the job sequence of the energy consumption cost acquisition workpiece of workpiece regulation time; 3rd algorithm (ESPRA), in conjunction with the advantage of EPRA and ESRA algorithm, builds virtual workpiece by ESRA algorithm, and EPRA algorithm obtains the processing sequence of virtual workpiece;
S4, above-mentioned three kinds of algorithms to be verified, propose two lower bounds of this problem, devise a l-G simulation test based on split plot experiment;
S5, by carrying out factor analysis to simulation result, Algorithm Analysis, lower bound analysis and CPU analyze working time, and analysis result shows: all principal elements reveal appreciable impact to object table except algorithm factor; ESPRA Algorithm for Solving effect is best in these three kinds of algorithms; LB1 is better than LB2; The working time of ESPRA algorithm is significantly smaller than other two kinds of algorithms.
2. the flexible Flow Shop energy optimization dispatching method that regulation time as claimed in claim 1 is relevant to order, it is characterized in that, described NEH algorithm comprises the steps:
Step 1: sort according to the decreasing order that workpiece is always processed, obtains work pieces process queue S;
Step 2: according to processing queue S, gets its first two workpiece and carries out scheduling and obtain optimal scheduling;
Step 3: read next workpiece according to processing queue S, is inserted into this workpiece certain position in the workpiece arrangement of having dispatched, makes regulation index minimum;
Step 4: repeat said process, until all workpiece in processing queue are all dispatched complete.
3. the flexible Flow Shop energy optimization dispatching method that regulation time as claimed in claim 1 is relevant to order, it is characterized in that, described ESRA algorithm comprises the steps:
Step 1: build energy consumption matrix ESST, the energy consumption free time cost total according to ESST matrix computations workpiece also sorts to workpiece according to its ascending order, obtains work pieces process order S;
Step 2: read the first two workpiece in processing queue S and carry out optimal scheduling according to objective function, obtaining partial scheduling result OP, workpiece is deleted from queue S;
Step 3: from O=3 to n, reads processing queue S o workpiece, then workpiece o is inserted into o possible position in OP, finally selects optimum local scheduling scheme as the processing queue of workpiece
oP * ;
Step 4: according to processing queue OP * and EST rule, arranges workpiece to process on every platform machine in each stage.
4. the flexible Flow Shop energy optimization dispatching method that regulation time as claimed in claim 1 is relevant to order, it is characterized in that, described ESPRA algorithm comprises the steps:
Step 1: initialization local scheduling scheme calculates OP*=0;
Step 2: build ESST matrix;
Step 3: according to ESST matrix, workpiece sorts according to the total idle energy consumption cost ascending order based on regulation time, obtains work pieces process queue S;
Step 4: according to processing queue S, builds virtual workpiece collection, calculates the process time of each virtual workpiece;
Step 5: decreasing order process time according to virtual workpiece sorts to virtual workpiece, obtains the processing queue σ of virtual workpiece;
Step 6: read two virtual workpieces before σ, process to the machine in per stage according to EST regulation arrangement workpiece, the scheduling scheme assignment of minimum energy consumption cost to OP*, and this virtual workpiece is deleted from σ;
Step 7: consider the next virtual workpiece in σ;
Step 8: virtual workpiece to be inserted in OP* all possible position and to find energy consumption cost that scheduling scheme minimum, assignment to OP *, and this virtual workpiece being deleted from σ;
Step 9: if walk 10 steps, otherwise forward step 7 to;
Step 10: the total energy consumption cost returned.
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Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104808636A (en) * | 2015-04-28 | 2015-07-29 | 广东工业大学 | Flexible flow shop energy consumption optimization scheduling method |
| CN105700495A (en) * | 2016-01-13 | 2016-06-22 | 济南大学 | Flexible job shop scheduling machine selection method based on processing time grade |
| CN106020142A (en) * | 2016-05-16 | 2016-10-12 | 佛山市南海区广工大数控装备协同创新研究院 | Flexible job shop scheduling method considering energy consumption cost and weighted tardiness cost |
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| CN109409774A (en) * | 2018-11-14 | 2019-03-01 | 合肥工业大学智能制造技术研究院 | Dispatching method, system and storage medium for intelligence manufacture digitlization workshop |
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| CN109918771B (en) * | 2019-03-05 | 2023-11-28 | 北京工业大学 | Energy-saving scheduling model of mixed flow forging workshop under multiple time factors |
| CN110705872A (en) * | 2019-09-30 | 2020-01-17 | 北京工业大学 | Production logistics scheduling analysis method for composite parallel processing |
| CN110825055A (en) * | 2019-11-26 | 2020-02-21 | 北京工业大学 | Hybrid production workshop energy-saving scheduling method considering continuous processing of heating furnace |
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