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nexedi
dream
Commits
08f6c5f7
Commit
08f6c5f7
authored
Oct 16, 2014
by
Georgios Dagkakis
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progress to new assignment method
parent
2c9a134b
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1
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dream/simulation/opAss_LPmethod.py
dream/simulation/opAss_LPmethod.py
+152
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dream/simulation/opAss_LPmethod.py
View file @
08f6c5f7
...
@@ -4,53 +4,172 @@ Created on 2 Jul 2014
...
@@ -4,53 +4,172 @@ Created on 2 Jul 2014
@author: Anna
@author: Anna
'''
'''
def
opAss_LP
(
stationList
,
PBlist
,
PBskills
):
def
opAss_LP
(
machineList
,
PBlist
,
PBskills
,
previousAssignment
=
{}):
'''
classdocs
from
pulp
import
LpProblem
,
LpMaximize
,
LpVariable
,
LpBinary
,
lpSum
,
LpStatus
'''
import
pulp
from
pulp
import
LpProblem
,
LpMaximize
,
LpVariable
,
LpBinary
,
lpSum
import
copy
machines
=
stationList
.
keys
()
import
glob
import
os
machines
=
machineList
.
keys
()
sumWIP
=
float
(
sum
([
machineList
[
mach
][
'WIP'
]
for
mach
in
machines
]))
weightFactors
=
[
2
,
1
,
0.5
,
1.5
]
# define LP problem
# define LP problem
prob
=
LpProblem
(
"PBassignment"
,
LpMaximize
)
prob
=
LpProblem
(
"PBassignment"
,
LpMaximize
)
# declare variables...binary assignment variables (operator i to machine j)
# declare variables...binary assignment variables (operator i to machine j)
PB_ass
=
LpVariable
.
dicts
(
'PB'
,
[(
i
,
j
)
for
i
in
PBlist
PB_ass
=
LpVariable
.
dicts
(
'PB'
,
[(
oper
,
mach
)
for
oper
in
PBlist
for
mach
in
machines
if
machineList
[
mach
][
'stationID'
]
in
PBskills
[
oper
]]
,
0
,
1
,
cat
=
pulp
.
LpBinary
)
for
j
in
machines
]
,
0
,
1
,
LpBinary
)
# objective...assignment of PBs to stations with higher WIP...sum of WIP associated with stations where PB is assigned
# objective...assignment of PBs to stations with higher WIP...sum of WIP associated with stations where PB is assigned
obj1
=
[
stationList
[
st
][
'WIP'
]
*
PB_ass
[(
oper
,
st
)]
for
oper
in
PBlist
for
st
in
machines
]
obj
=
[
machineList
[
mach
][
'WIP'
]
*
PB_ass
[(
oper
,
mach
)]
*
weightFactors
[
0
]
/
float
(
sumWIP
)
for
oper
in
PBlist
for
mach
in
machines
if
machineList
[
mach
][
'stationID'
]
in
PBskills
[
oper
]]
prob
+=
lpSum
(
obj1
)
# second set of variables (delta assignment between stations) to facilitate the distribution of PBs across different stations
stationGroup
=
{}
for
mach
in
machines
:
if
machineList
[
mach
][
'stationID'
]
not
in
stationGroup
:
stationGroup
[
machineList
[
mach
][
'stationID'
]]
=
[]
stationGroup
[
machineList
[
mach
][
'stationID'
]].
append
(
mach
)
Delta_Station
=
LpVariable
.
dicts
(
"D_station"
,[(
st1
,
st2
)
for
i1
,
st1
in
enumerate
(
stationGroup
.
keys
())
for
st2
in
stationGroup
.
keys
()[
i1
+
1
:]])
# calculate global max number of machines within a station that will be used as dividers for Delta_Station
maxNoMachines
=
0
for
st
in
stationGroup
:
if
len
(
stationGroup
[
st
])
>
maxNoMachines
:
maxNoMachines
=
len
(
stationGroup
[
st
])
# calculation of DeltaStation values
for
i
,
st1
in
enumerate
(
stationGroup
.
keys
()):
tempList
=
[]
for
mach1
in
stationGroup
[
st1
]:
for
oper1
in
PBlist
:
if
st1
in
PBskills
[
oper1
]:
tempList
.
append
(
PB_ass
[(
oper1
,
mach1
)]
/
float
(
maxNoMachines
))
for
st2
in
stationGroup
.
keys
()[
i
+
1
:]:
finalList
=
copy
.
copy
(
tempList
)
for
mach2
in
stationGroup
[
st2
]:
for
oper2
in
PBlist
:
if
st2
in
PBskills
[
oper2
]:
finalList
.
append
(
PB_ass
[(
oper2
,
mach2
)]
*-
1
/
float
(
maxNoMachines
))
prob
+=
lpSum
(
finalList
)
>=
Delta_Station
[(
st1
,
st2
)]
prob
+=
lpSum
([
i
*-
1
for
i
in
finalList
])
>=
Delta_Station
[(
st1
,
st2
)]
# integration of second obj
normalisingFactorDeltaStation
=
0
for
i
in
range
(
len
(
stationGroup
)):
normalisingFactorDeltaStation
+=
i
for
i1
,
st1
in
enumerate
(
stationGroup
.
keys
()):
for
st2
in
stationGroup
.
keys
()[
i1
+
1
:]:
obj
.
append
(
Delta_Station
[(
st1
,
st2
)]
*
weightFactors
[
1
]
/
float
(
normalisingFactorDeltaStation
)
)
# min variation in PB assignment
Delta_Assignment
=
[]
OldAss
=
{}
for
pb
in
previousAssignment
:
if
pb
in
PBlist
:
for
station
in
PBskills
[
pb
]:
for
mach
in
machineList
:
if
machineList
[
mach
][
'stationID'
]
==
station
:
Delta_Assignment
.
append
([
pb
,
mach
])
if
previousAssignment
[
pb
]
==
mach
:
OldAss
[(
pb
,
mach
)]
=
1
else
:
OldAss
[(
pb
,
mach
)]
=
0
# create delta assignment variables
Delta_Ass
=
LpVariable
.
dicts
(
"D_Ass"
,[(
d
[
0
],
d
[
1
])
for
d
in
Delta_Assignment
])
# integration of third objective
for
d
in
Delta_Assignment
:
obj
.
append
(
Delta_Ass
[(
d
[
0
],
d
[
1
])]
*
(
-
1.0
*
weightFactors
[
2
]
/
(
2
*
len
(
previousAssignment
)))
)
# calculation of Delta_Ass
for
d
in
Delta_Assignment
:
if
OldAss
[(
d
[
0
],
d
[
1
])]
==
1
:
prob
+=
lpSum
(
OldAss
[(
d
[
0
],
d
[
1
])]
-
PB_ass
[(
d
[
0
],
d
[
1
])])
<=
Delta_Ass
[(
d
[
0
],
d
[
1
])]
else
:
prob
+=
lpSum
(
PB_ass
[(
d
[
0
],
d
[
1
])]
-
OldAss
[(
d
[
0
],
d
[
1
])])
<=
Delta_Ass
[(
d
[
0
],
d
[
1
])]
# 4th obj = fill a subline
# verify whether there are machines active in the sublines
subline
=
{
0
:{
'noMach'
:
0
,
'WIP'
:
0
},
1
:{
'noMach'
:
0
,
'WIP'
:
0
}}
for
mach
in
machineList
:
if
machineList
[
mach
][
'stationID'
]
in
[
0
,
1
,
2
]:
subline
[
machineList
[
mach
][
'machineID'
]][
'noMach'
]
+=
1
subline
[
machineList
[
mach
][
'machineID'
]][
'WIP'
]
+=
machineList
[
mach
][
'WIP'
]
chosenSubLine
=
False
# choose subline to be filled first
if
subline
[
0
][
'noMach'
]
==
3
:
# case when both sublines are fully active
if
subline
[
1
][
'noMach'
]
==
3
:
if
subline
[
0
][
'WIP'
]
>=
subline
[
1
][
'WIP'
]:
chosenSubLine
=
1
else
:
chosenSubLine
=
2
else
:
chosenSubLine
=
1
elif
subline
[
1
][
'noMach'
]
==
3
:
chosenSubLine
=
2
#create variable for the chosen subline
if
chosenSubLine
:
chosenSubLine
-=
1
subLine
=
LpVariable
(
'SubL'
,
lowBound
=
0
)
sub
=
[]
for
station
in
range
(
3
):
mach
=
G
.
Tool
[
station
][
chosenSubLine
].
name
#'St'+str(station)+'_M'+str(chosenSubLine)
for
oper
in
PBlist
:
if
station
in
PBskills
[
oper
]:
sub
.
append
(
PB_ass
[(
oper
,
mach
)])
prob
+=
lpSum
(
sub
)
>=
subLine
chosenSubLine
+=
1
obj
.
append
(
subLine
*
weightFactors
[
3
]
/
3.0
)
prob
+=
lpSum
(
obj
)
# constraint 1: # operators assigned to a station <= 1
# constraint 1: # operators assigned to a station <= 1
for
machine
in
machines
:
for
machine
in
machines
:
prob
+=
lpSum
([
PB_ass
[(
oper
,
machine
)]
for
oper
in
PBlist
])
<=
1
prob
+=
lpSum
([
PB_ass
[(
oper
,
machine
)]
for
oper
in
PBlist
if
machineList
[
machine
][
'stationID'
]
in
PBskills
[
oper
]
])
<=
1
# constraint 2: # machines assigned to an operator <= 1
# constraint 2: # machines assigned to an operator <= 1
for
operator
in
PBlist
:
for
operator
in
PBlist
:
prob
+=
lpSum
([
PB_ass
[(
operator
,
machine
)]
for
machine
in
machines
])
<=
1
prob
+=
lpSum
([
PB_ass
[(
operator
,
machine
)]
for
machine
in
machines
if
machineList
[
machine
][
'stationID'
]
in
PBskills
[
operator
]])
<=
1
# constraint 3: assign operator that are capable of running a machine
skills
=
{}
for
mach
in
machines
:
for
oper
in
PBlist
:
if
stationList
[
mach
][
'stationID'
]
in
PBskills
[
oper
]:
skills
[(
mach
,
oper
)]
=
1
else
:
skills
[(
mach
,
oper
)]
=
0
prob
+=
lpSum
([
skills
[(
mach
,
oper
)]
-
PB_ass
[(
oper
,
mach
)]])
>=
0
# write the problem data to an .lp file.
prob
.
writeLP
(
"PBassignment.lp"
)
prob
.
solve
()
prob
.
solve
()
solution
=
{}
if
LpStatus
[
prob
.
status
]
!=
'Optimal'
:
print
'WARNING: LP solution '
,
LpStatus
[
prob
.
status
]
PBallocation
=
{}
for
mach
in
machines
:
for
mach
in
machines
:
for
oper
in
PBlist
:
for
oper
in
PBlist
:
if
PB_ass
[(
oper
,
mach
)].
varValue
>
0.00001
:
if
machineList
[
mach
][
'stationID'
]
in
PBskills
[
oper
]:
# print 'PB', oper, 'assigned to machine', mach
if
PB_ass
[(
oper
,
mach
)].
varValue
>
0.00001
:
solution
[
str
(
oper
)]
=
str
(
mach
)
PBallocation
[
oper
]
=
mach
return
solution
files
=
glob
.
glob
(
'*.mps'
)
for
f
in
files
:
os
.
remove
(
f
)
files
=
glob
.
glob
(
'*.lp'
)
for
f
in
files
:
os
.
remove
(
f
)
return
PBallocation
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