Folio - Modelling examples from 'Getting started'
Description
- Chapter 3 Inputting and Solving a Linear Programming problem
- foliolp.mos: modeling and solving a small LP problem
- foliolperr.mos: LP model with syntax errors
- foliolps.mos: LP model using string indices
- Chapter 4 Working with data
- foliodata.mos (data file: folio.dat): data input from file, result
output to a file, model parameters
- folioodbc.mos (data files: folio.xls, folio.mdb, folio.sqlite): data input
from a spreadsheet or database, result output to a spreadsheet or database,
model parameters
- folioexcel.mos (data file: folio.xls): same as folioodbc.mos but
with Excel-specific data input and output (Windows only)
- foliosheet.mos (data file: folio.xls): same as folioodbc.mos but
with data input and output through generic spreadsheet access
- foliocsv.mos (data file: folio.csv): same as folioodbc.mos but
with data input and output through generic spreadsheet access in CSV format
- Chapter 5 Drawing user graphs
- folioloop.mos (data files: folio.dat, foliodev.dat): re-solving with
varied parameter settings
- folioloop_graph.mos (data files: folio.dat, foliodev.dat): re-solving with
varied parameter settings, graphical solution display
- foliolps_graph.mos: same as foliolps, adding graphical solution display
- Chapter 6 Mixed Integer Programming
- foliomip1.mos (data file: folio.dat): modeling and solving a small
MIP problem (binary variables)
- foliomip2.mos (data file: folio.dat): modeling and solving a small
MIP problem (semi-continuous variables)
- Chapter 7 Quadratic Programming
- folioqp.mos (data file: folioqp.dat): modeling and solving a QP and
a MIQP problem
- folioqp_graph.mos (data files: folioqp.dat, folioqpgraph.dat):
re-solving a QP problem with varied parameter settings, graphical solution
display
- folioqc.mos (data file: folioqp.dat): modeling and solving a QCQP and
- foliomiqc.mos (data file: folioqp.dat): modeling and solving a MIQCQP
- Chapter 8 Heuristics
- folioheur.mos (data file: folio.dat): heuristic solution of a MIP problem
Source Files
Data Files
folioodbc.mos
(!******************************************************
Mosel Example Problems
======================
file folioodbc.mos
``````````````````
Modeling a small LP problem
to perform portfolio optimization.
-- Parameters, data input through ODBC,
result output through ODBC --
IMPORTANT:
If this example is run more than once,
you need to delete the solution data from the
previous run in the database/spreasheet.
(c) 2008 Fair Isaac Corporation
author: S.Heipcke, Mar. 2006, rev. Sep. 2014
*******************************************************!)
model "Portfolio optimization with LP (ODBC)"
uses "mmxprs", "mmodbc"
parameters
DATAFILE = "folio.mdb" ! Access database with problem data
! DATAFILE = "folio.sqlite" ! SQLite database with problem data
DBDATA = "folio" ! Database table with problem data
DBSOL = "foliosol" ! Table for solution data
MAXRISK = 1/3 ! Max. investment into high-risk values
MAXVAL = 0.3 ! Max. investment per share
MINAM = 0.5 ! Min. investment into N.-American values
end-parameters
declarations
SHARES: set of string ! Set of shares
RET: array(SHARES) of real ! Estimated return in investment
RISK: array(SHARES) of boolean ! List of high-risk values among shares
NA: array(SHARES) of boolean ! List of shares issued in N.-America
end-declarations
! Data input from database
initializations from "mmodbc.odbc:" + DATAFILE
[RET,RISK,NA] as DBDATA
end-initializations
declarations
frac: array(SHARES) of mpvar ! Fraction of capital used per share
end-declarations
! Objective: total return
Return:= sum(s in SHARES) RET(s)*frac(s)
! Limit the percentage of high-risk values
sum(s in SHARES | RISK(s)) frac(s) <= MAXRISK
! Minimum amount of North-American values
sum(s in SHARES | NA(s)) frac(s) >= MINAM
! Spend all the capital
sum(s in SHARES) frac(s) = 1
! Upper bounds on the investment per share
forall(s in SHARES) frac(s) <= MAXVAL
! Solve the problem
maximize(Return)
! Solution printing
writeln("Total return: ", getobjval)
forall(s in SHARES)
writeln(strfmt(s,-12), ": \t", strfmt(getsol(frac(s))*100,5,2), "%")
! Solution output to database
declarations
Solfrac: array(SHARES) of real ! Solution values
end-declarations
forall(s in SHARES) Solfrac(s):= getsol(frac(s))*100
! Optional: Clean up previous results (works only for databases, cannot
! be used with spreadsheets).
! Alternatively, delete data (by hand) directly in the database.
SQLconnect(DATAFILE)
SQLexecute("delete from " + DBSOL)
SQLdisconnect
! Data output to database
initializations to "mmodbc.odbc:" + DATAFILE
Solfrac as DBSOL
end-initializations
end-model
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