Problem 1. Maximizing net present value with budget constraint
Mathematical Problem Statement
Problem dimension and solving time
Solution in Run-File Environment
Solution in MATLAB Environment
Problem 2. Maximizing net present value with constraint on available initial capital
Mathematical Problem Statement
Problem dimension and solving time
Solution in Run-File Environment
Solution in MATLAB Environment
This case study demonstrates an optimization setup for a project selection problem. A similar problem is described in Luenberger (1998), p. 104. The model allows selecting among several different projects. Each project, if chosen, requires an initial capital outlay. Projects are selected to maximize the net present value of the investment subject to constraint on the initial available capital. This problem belongs to the class of “knapsack optimization” problem. We present two equivalent problem formulations: in the first one we use the PSG “linear” function with decision variables of type Boolean, in the second one the value of the items placed to the knapsack is calculated with PSG “fxchg_pos” function.
Maximize Linear (maximizing net present value)
subject to
Linear ≤ Const1 (budget constraint)
Box constraints (binary position variables, x = Boolean)
where
Box constraints = constraints on individual decision variables
Mathematical Problem Statement
Problem dimension and solving time
Number of Variables |
7 |
Number of Scenarios |
1 |
Objective Value |
610 |
Solving Time (sec) |
0.01 |
Solution in Run-File Environment
Input Files to run CS:
Output Files:
Solution in MATLAB Environment
Solved with PSG MATLAB subroutine riskprog and function tbpsg_run (General (Text) Format of PSG in MATLAB):
Input Files to run CS:
Maximize Linear (maximizing net present value)
subject to
Fxchg ≤ Const2 (constraint on available initial capital)
Box constraints (bounds on positions)
where
Fxchg = Fixed Charge
Box constraints = constraints on individual decision variables
Mathematical Problem Statement
Problem dimension and solving time
Number of Variables |
7 |
Number of Scenarios |
1 |
Objective Value |
610 |
Solving Time (sec) |
0.01 |
Solution in Run-File Environment
Input Files to run CS:
Output Files:
Solution in MATLAB Environment
Solved with PSG MATLAB subroutine riskprog and function tbpsg_run (General (Text) Format of PSG in MATLAB):
Input Files to run CS:
[1] Luenberger, D.G. (1998): Investment Science, Oxford University Press, 494 p.