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Folio - Advanced modelling and solving tasks

Description
Advanced modelling and solving tasks for a portfolio optimization problem:
  • Automated solver tuning (foliolptune.mos)
  • Defining an integer solution callback (foliocb.mos)
  • Using the solution enumerator for multiple MIP solutions (folioenumsol.mos)
  • Handling infeasibility
    • handling infeasibility through deviation variables (folioinfeas.mos)
    • retrieving infeasible row/column from presolve (folioinfcause.mos)
    • retrieving IIS - LP or MIP infeasible (folioiis.mos, foliomiis.mos)
    • using the built-in infeasibility repair functionality (foliorep.mos)
    • same as foliorep, using an 'mpsol' object (foliorep_sol.mos)
  • Data transfer in memory
    • running foliomemio.mos with data transfer in memory (runfolio.mos)
    • same running foliomemio2.mos, grouping tables with identical index sets in "initializations" blocks (runfolio2.mos)
    • master model running several model instances in parallel (runfoliopar.mos)
  • Remote models on a distributed architecture
    • running foliomemio.mos on a remote instance of Mosel (runfoliodistr.mos)
    • master model running several model instances in parallel, each on a different (remote) instance of Mosel (runfoliopardistr.mos)
  • Remote execution via XPRD
    • See examples in the Mosel Whitepapers directory moselpar/XPRD
  • XML and JSON data formats
    • reading data from an XML file, solution output in XML format on screen and to a new file (folioxml.mos, folioxmlqp.mos)
    • generate HTML output file as an XML document (runfolioxml.mos)
    • using JSON-format data files, reading data from a JSON file, solution output in JSON format on screen and to a new file (foliojson.mos)
  • HTTP
    • starting an HTTP server managing requests from HTTP clients (foliohttpsrv.mos)
    • HTTP client exchanging XML data files with an HTTP server (foliohttpclient.mos)


Source Files

Data Files





folioinfcause.mos

(!******************************************************
   Mosel Example Problems
   ======================

   file folioinfcause.mos
   ``````````````````````
   Modeling a MIP problem 
   to perform portfolio optimization.

   Same model as in foliomip3.mos.
   -- Infeasible model parameter values --
   -- Retrieving infeasible row/column from presolve --

   (c) 2012 Fair Isaac Corporation
       author: S.Heipcke, Oct. 2012, rev. May 2018
*******************************************************!)

model "Portfolio optimization with MIP"
 uses "mmxprs"

 parameters
  MAXRISK = 1/3                     ! Max. investment into high-risk values
  MINREG = 0.1                      ! Min. investment per geogr. region
  MAXREG = 0.2                      ! Max. investment per geogr. region
  MAXSEC = 0.1                      ! Max. investment per ind. sector
  MAXVAL = 0.15                     ! Max. investment per share
  MINVAL = 0.15                     ! Min. investment per share
  MAXNUM = 4                        ! Max. number of different assets
  DATAFILE = "folio10.dat"          ! File with problem data
 end-parameters

 forward procedure print_sol

 declarations
  SHARES: set of string              ! Set of shares
  RISK: set of string                ! Set of high-risk values among shares
  REGIONS: set of string             ! Geographical regions
  TYPES: set of string               ! Share types (ind. sectors)
  LOC: array(REGIONS) of set of string ! Sets of shares per geogr. region
  RET: array(SHARES) of real         ! Estimated return in investment
  SEC: array(TYPES) of set of string ! Sets of shares per industry sector
 end-declarations

 initializations from DATAFILE
  RISK RET LOC SEC
 end-initializations

 public declarations
  frac: array(SHARES) of mpvar      ! Fraction of capital used per share
  buy: array(SHARES) of mpvar       ! 1 if asset is in portfolio, 0 otherwise
  Return: linctr                    ! Total return
  LimitRisk: linctr                 ! Max. percentage of high-risk values
  LimitMinReg,LimitMaxReg: array(REGIONS) of linctr  ! Min/max perc. per region
  LimitSec: array(TYPES) of linctr  ! Max. percentage per industry sector
  TotalOne: linctr                  ! Spend all the capital
  LimitNum: linctr                  ! Max. total number of assets
  LinkUB,LinkLB: array(SHARES) of linctr  ! Linking buy+frac variables
 end-declarations

! Objective: total return
 Return:= sum(s in SHARES) RET(s)*frac(s) 

! Limit the percentage of high-risk values
 LimitRisk:= sum(s in RISK) frac(s) <= MAXRISK

! Limits on geographical distribution
 forall(r in REGIONS) do
  LimitMinReg(r):= sum(s in LOC(r)) frac(s) >= MINREG
  LimitMaxReg(r):= sum(s in LOC(r)) frac(s) <= MAXREG
 end-do 

! Diversification across industry sectors
 forall(t in TYPES) LimitSec(t):= sum(s in SEC(t)) frac(s) <= MAXSEC

! Spend all the capital
 TotalOne:= sum(s in SHARES) frac(s) = 1
 
! Upper bounds on the investment per share
 forall(s in SHARES) frac(s) <= MAXVAL

! Limit the total number of assets
 LimitNum:= sum(s in SHARES) buy(s) <= MAXNUM

 forall(s in SHARES) do
  buy(s) is_binary                  ! Turn variables into binaries
  LinkUB(s):= frac(s) <= MAXVAL*buy(s)     ! Linking the variables
  LinkLB(s):= frac(s) >= MINVAL*buy(s)     ! Linking the variables
 end-do


! Display Optimizer log
 setparam("XPRS_verbose", true)
 setparam("XPRS_LOADNAMES", true)

 setparam("XPRS_TRACE", 1)          ! Show detailed presolve log

! Solve the problem
 maximize(XPRS_LIN,Return)

 declarations
  V: set of mpvar
  C: set of linctr
 end-declarations

 probstat:= getprobstat
 case probstat of
  XPRS_OPT: do
              writeln("Problem solved")
              print_sol
            end-do
  XPRS_INF: do
              setparam("XPRS_verbose", false)  ! Disable Optimizer output
	      writeln("LP infeasible")
               
              getinfcause(V, C)                ! Retrieve inf. var. or constr.
              forall(v in V) writeln("Infeasible variable: ", getname(v), " ")
              forall(c in C) writeln("Infeasible constraint: ", getname(c), " ")
            end-do
  XPRS_OTH: writeln("Problem unbounded") 
  XPRS_UNF: writeln("Optimization unfinished")
  else writeln("Unknown problem status")
 end-case

! Solution printing
 procedure print_sol
  writeln("Solution ", getparam("XPRS_MIPSOLS"))
  writeln("Total return: ", getsol(Return))
  forall(s in SHARES | getsol(frac(s))>0)
   writeln(s, ": ", getsol(frac(s))*100, "% (", getsol(buy(s)), ")")
 end-procedure
end-model 

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