Initializing help system before first use

Formulating the Mosel Model

Even if you are not a Mosel expert, you should be able to glean the intent of this code sample if you have some programming experience.
Copy and paste the code into your own editor. The source file is available in the examples folder in your Xpress installation directory.
Note The following code fragment contains line numbers, so that they can be referenced in the subsequent commentary. 
01:	(!
02:	Portfolio optimization app example
03:	(c) 2020 Fair Isaac Corporation.
04:	!)
05:	model "Portfolio Optimization"
06:	  version 1.0.0
07:	
08:	  options noimplicit	
09:	  
10:	  uses "mmxprs"
11:	
12:	  declarations
13:	    ! Constant
14:	    DATAFILE = "shares.csv"
15:	  end-declarations
16:	  
17:	  ! Declaration of the scenario data model for input and results
18:	  public declarations
19:	    ! Input entities	    
20:	    MaxHighRisk: real	    
21:	    MaxPerShare: real    
22:	    MinNorthAmerica: real	    
23:	    ShareIds: set of string
24:	
25:	    ! Input and result entities indexed over ShareIds
26:	    Shares_Return: array(ShareIds) of real
27:	    Shares_HighRisk: array(ShareIds) of boolean
28:	    Shares_NorthAmerica: array(ShareIds) of boolean
29:	    Shares_fraction: array(ShareIds) of mpvar
30:	
31:	    ! Result entities
32:	    TotalReturn: linctr
33:	  end-declarations
34:	
35:	  public procedure loaddata
36:	    writeln("Loading data.")
37:	    MaxHighRisk := 0.33  ! Max. investment into high-risk values
38:	    MaxPerShare := 0.25    ! Max. investment per share
39:	    MinNorthAmerica := 0.45	! Min. investment into N.-American values
40:	
41:	    initializations from "mmsheet.csv:skiph;" + DATAFILE
42:	      [Shares_Return, Shares_HighRisk, Shares_NorthAmerica] as '[A:D]'
43:	    end-initializations
44:	
45:	    writeln("Loading finished.")
46:	  end-procedure
47:	
48:	  procedure solvemodel
49:	    declarations
50:	      LimitHighRisk, LimitNorthAmerica 
					 : linctr
51:	    end-declarations
52:	    	
53:	    ! Objective: expected total return
54:	    TotalReturn := sum(s in ShareIds) Shares_Return(s) * Shares_fraction(s)
55:	
56:	    ! Limit the percentage of high-risk values
57:	    LimitHighRisk :=
58:	      sum(s in ShareIds | Shares_HighRisk(s)) Shares_fraction(s) <= MaxHighRisk
59:	
60:	    ! Minimum amount of North-American values
61:	    LimitNorthAmerica 
					  :=
62:	      sum(s in ShareIds | Shares_NorthAmerica(s)) Shares_fraction(s) >= MinNorthAmerica
63:	
64: 	    ! Spend all the capital
65: 	    sum(s in ShareIds) Shares_fraction(s) = 1
66: 	
67: 	    ! Upper bounds on the investment per share
68: 	    forall(s in ShareIds) do
69: 	      Shares_fraction(s) <= MaxPerShare
70: 	    end-do
71:	
72: 	    writeln('Starting optimization.')
73:	    
74: 	    ! Solve optimization problem
75: 	    maximize(TotalReturn)
76:	
77: 	    writeln('Optimization finished.')
78: 	  end-procedure
79:	  
80: 	  loaddata
81: 	  solvemodel
82:	
83: 	end-model

Commentary

Lines 12-33 contain the entity declarations.

Lines 35-46 establish the model's runtime parameters. The specified default values can be changed for every model execution without any need to edit the model source.

Line 41-43 initializes the entities with values from an external data file in csv format called shares.csv (specified on line 14) which contains the following data: 
! Data file for ‘shares.csv’
shareIds,returnOnInvestment,highRisk,northAmerica
Bank,6.0,False,False
Brewery,8.0,False,False
Cars,7.0,False,False
Electronics,21.0,True,False
Hardware,17.0,True,True
Highways,9.0,False,False
Software,31.0,True,False
Telecom,12.0,True,True
Theater,26.0,True,True
Treasury,5.0,False,True
Note The shares.csv file is a representation of the preferences made by the investor in the section Introducing the Example Business Problem.

Line 54 contains an expression whose value is assigned to an entity called TotalReturn - the goal of the problem is ultimately to maximize this expression.

Lines 55-71 establish the constraints of the problem, while line 75 starts the optimization solver to maximize the value of TotalReturn.

Finally, lines 80 and 81 read the source data file and run the optimization.

Parent Topic Using Mosel to Model the Example Business Problem

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