WOLF ENERGY SA
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Engineering & Technology

 

LINEAR PROGRAMMING

MAIN FEATURES

  • Selection of an unlimited number of linear functions for each analysis
  • Definition of each function Y in the N dimensional space X_1,..., X_N
  • Definition of M linear constraints (equalities or inequalities) in the N dimensional space X_1,..., X_N
  • Computation of discrete function domains through construction of N dimensional grids
  • Search of minimal or maximal solution for the objective function Y defined within the grid points
  • Comparison of analytical results with available field data
  • Visualisation of results
  • Suitable for designing and testing

OPTIONS FOR IO OPERATIONS

  • Microsoft Excel Spreadsheet Files (xlsx)

OPTIONS FOR GRAPHICS

  • Standard Image Formats (jpeg, tiff)
  • Portable Document Format (pdf)

TEST CASES

Suppose we want to understand which is the distribution of the Y variable defined as:

  • Y= C_1 * X_1+ ...+ C_N * X_N

with the constraints:

  •  X_1 + ... + X_N = 1
  • min(X_1)<=X_1<=max(X_1)
  • ...
  • min(X_N)<=X_N<=max(X_N)

and with C_1,...,C_N which are given constants.

Figure 1 compares simulation results coming for different discretisation of the original function.

Figure 1. Empirical CDF (Y-Axis) versus outcome variable (X-Axis).

DELIVERABLES


User's Manual

PDF



AVI