(!****************************************************************
CP example problems
===================
file a4sugar_ka.mos
```````````````````
Production of cane sugar
(See "Applications of optimization with Xpress-MP",
Section 6.4 Cane sugar production)
Assignment with resource-dependent cost.
Wagen loads need to be assigned time slots on production
lines. The limit on the number of resources (= production lines)
is modeled by counting the 'occurrence' of the time slot values
in the assigment variables 'process'.
(c) 2008 Artelys S.A. and Fair Isaac Corporation
*****************************************************************!)
model "A-4 Cane sugar production (CP)"
uses "kalis"
declarations
NW = 11 ! Number of wagon loads of sugar
NL = 3 ! Number of production lines
WAGONS = 1..NW
NS = ceil(NW/NL)
SLOTS = 1..NS ! Time slots for production
LOSS: array(WAGONS) of integer ! Loss in kg/hour
LIFE: array(WAGONS) of integer ! Remaining time per lot (in hours)
DUR: integer ! Duration of the production (in hours)
COST: array(SLOTS) of integer ! Cost per wagon
loss: array(WAGONS) of cpvar ! Loss per wagon
process: array(WAGONS) of cpvar ! Time slots for wagon loads
totalLoss: cpvar ! Objective variable
end-declarations
initializations from 'Data/a4sugar.dat'
LOSS LIFE DUR
end-initializations
forall(w in WAGONS) setdomain(process(w), 1, NS)
! Wagon loads per time slot
forall(s in SLOTS) occurrence(s, process) <= NL
! Limit on raw product life
forall(w in WAGONS) process(w) <= floor(LIFE(w)/DUR)
! Objective function: total loss
forall(w in WAGONS) do
forall(s in SLOTS) COST(s):= s*DUR*LOSS(w)
loss(w) = element(COST, process(w))
end-do
totalLoss = sum(w in WAGONS) loss(w)
cp_set_branching(assign_var(KALIS_SMALLEST_MAX, KALIS_MIN_TO_MAX, process))
! Solve the problem
if not (cp_minimize(totalLoss)) then
writeln("No solution found")
exit(0)
end-if
! Solution printing
writeln("Total loss: ", getsol(totalLoss))
forall(s in SLOTS) do
write("Slot ", s, ": ")
forall(w in WAGONS)
if(getsol(process(w))=s) then
write("wagon ", strfmt(w,2), strfmt(" (" + s*DUR*LOSS(w) + ") ", 8))
end-if
writeln
end-do
end-model
|
(!****************************************************************
CP example problems
===================
file a4sugar2_ka.mos
````````````````````
Production of cane sugar
(See "Applications of optimization with Xpress-MP",
Section 6.4 Cane sugar production)
Assignment with resource-dependent cost.
Wagen loads need to be assigned time slots on production
lines. The limit on the number of resources (= production lines)
is modeled by counting the 'occurrence' of the time slot values
in the assigment variables 'process'.
- Alternative formulation using 'distribute' constraint -
(c) 2008 Artelys S.A. and Fair Isaac Corporation
*****************************************************************!)
model "A-4 Cane sugar production (CP) - 2"
uses "kalis"
declarations
NW = 11 ! Number of wagon loads of sugar
NL = 3 ! Number of production lines
WAGONS = 1..NW
NS = ceil(NW/NL)
SLOTS = 1..NS ! Time slots for production
LOSS: array(WAGONS) of integer ! Loss in kg/hour
LIFE: array(WAGONS) of integer ! Remaining time per lot (in hours)
DUR: integer ! Duration of the production (in hours)
COST: array(SLOTS) of integer ! Cost per wagon
MINUSE,MAXUSE: array(SLOTS) of integer ! Lower and upper bounds on slot use
loss: array(WAGONS) of cpvar ! Loss per wagon
process: array(WAGONS) of cpvar ! Time slots for wagon loads
totalLoss: cpvar ! Objective variable
end-declarations
initializations from 'Data/a4sugar.dat'
LOSS LIFE DUR
end-initializations
forall(w in WAGONS) setdomain(process(w), 1, NS)
! Wagon loads per time slot
forall(s in SLOTS) MAXUSE(s):= NL
distribute(process, SLOTS, MINUSE, MAXUSE)
! Limit on raw product life
forall(w in WAGONS) process(w) <= floor(LIFE(w)/DUR)
! Objective function: total loss
forall(w in WAGONS) do
forall(s in SLOTS) COST(s):= s*DUR*LOSS(w)
loss(w) = element(COST, process(w))
end-do
totalLoss = sum(w in WAGONS) loss(w)
cp_set_branching(assign_var(KALIS_SMALLEST_MAX, KALIS_MIN_TO_MAX, process))
! Solve the problem
if not (cp_minimize(totalLoss)) then
writeln("No solution found")
exit(0)
end-if
! Solution printing
writeln("Total loss: ", getsol(totalLoss))
forall(s in SLOTS) do
write("Slot ", s, ": ")
forall(w in WAGONS)
if(getsol(process(w))=s) then
write("wagon ", strfmt(w,2), strfmt(" (" + s*DUR*LOSS(w) + ") ", 8))
end-if
writeln
end-do
end-model
|
