Planning problems
Description
| Problem name and type, features | Difficulty | Related examples |
| C‑1 | Planning the production of bicycles: Production planning (single product) | *** | |
|---|
| modeling inventory balance; inline if, forall-do |
| C‑2 | Production of drinking glasses: Multi-item production planning | ** | prodplan_graph.mos |
|---|
| modeling stock balance constraints; inline if, index value 0 |
| C‑3 | Material requirement planning: Material requirement planning (MRP) | ** | |
|---|
| working with index (sub)sets, dynamic initialization, automatic finalization, as |
| C‑4 | Planning the production of electronic components: Multi-item production planning | ** | c2glass.mos |
|---|
| modeling stock balance constraints; inline if |
| C‑5 | Planning the production of fiberglass: Production planning with time-dependent production cost | *** | transship_graph.mos |
|---|
| representation of multi-period production as flow; encoding of arcs, exists, create, isodd, getlast, inline if |
| C‑6 | Assignment of production batches to machines: Generalized assignment problem | * | assignment_graph.mos |
|---|
Further explanation of this example:
'Applications of optimization with Xpress-MP', Chapter 8: Production planning
Source Files
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Data Files
c1bike.mos
(!******************************************************
Mosel Example Problems
======================
file c1bike.mos
```````````````
Planning the production of bicycles
A sales forecast shows the predicted bicycle demand for the
upcoming year. There is a set production capacity per month
but it can be increased with overtime (with additional costs).
The company can store excess bikes at a small cost with no
limit to quantity. How many bikes need to be produced and
stored in the next year to meet the forecasted demand while
minimizing total (production, overtime, storage) cost?
This implementation using the inline 'if' function to condense
the balance constraints since this varies for t=1 and t>1.
Note that there is no slack built into the demand forecast so
bike storage will be as low as possible to reduce total cost.
This may not be practical if there is an unpredicted spike in
demand.
(c) 2008-2022 Fair Isaac Corporation
author: S. Heipcke, Mar. 2002, rev. Mar. 2022
*******************************************************!)
model "C-1 Bicycle production"
uses "mmxprs"
declarations
TIMES = 1..12 ! Range of time periods
DEM: array(TIMES) of integer ! Demand per months
CNORM,COVER: integer ! Prod. cost in normal / overtime hours
CSTOCK: integer ! Storage cost per bicycle
CAP: integer ! Monthly capacity in normal working hours
ISTOCK: integer ! Initial stock
pnorm:array(TIMES) of mpvar ! No. of bicycles produced in normal hours
pover:array(TIMES) of mpvar ! No. of bicycles produced in overtime hours
store:array(TIMES) of mpvar ! No. of bicycles stored per month
end-declarations
initializations from 'c1bike.dat'
DEM CNORM COVER CSTOCK CAP ISTOCK
end-initializations
! Objective: minimize production cost
Cost:= sum(t in TIMES) (CNORM*pnorm(t) + COVER*pover(t) + CSTOCK*store(t))
! Satisfy the demand for every period
forall(t in TIMES)
pnorm(t) + pover(t) + if(t>1, store(t-1), ISTOCK) = DEM(t) + store(t)
! Capacity limits on normal and overtime working hours per month
forall(t in TIMES) do
pnorm(t) <= CAP
pover(t) <= 0.5*CAP
end-do
! Solve the problem
minimize(Cost)
! Solution printing
declarations
MONTHS: array(TIMES) of string ! Names of months
end-declarations
initializations from 'c1bike.dat'
MONTHS
end-initializations
writeln("Total cost: ", getobjval)
write(" ")
forall(t in TIMES) write(strfmt(MONTHS(t),4))
setparam("realfmt", "%4g") ! Reserve 4 char.s for display of real numbers
write("\nDemand ")
forall(t in TIMES) write(DEM(t)/1000)
write("\nNormal ")
forall(t in TIMES) write(getsol(pnorm(t))/1000)
write("\nAdd. ")
forall(t in TIMES) write(getsol(pover(t))/1000)
write("\nStore ")
forall(t in TIMES) write(getsol(store(t))/1000)
writeln
end-model
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