Study on Linear Programming in Risk Management

The deterministic nature of the linear programming model is well-known. One method for dealing with uncertainty is to calculate the range of optimality. The effect of changing each objective function coefficient one at a time is studied after achieving the optimal solution (typically using the simplex approach). The optimality range is defined as the region in which the choice variables remain constant. This sensitivity analysis aids the analyst in gaining a better understanding of the problem. It is, however, impractical since the coefficients of objective functions do not tend to stay constant. They are frequently profit contributions from sold items, and their selling prices fluctuate at random. A realistic linear programme is built for simultaneously randomising the coefficients from any probability distribution. A novel method for creating a copula of random objective function coefficients based on a given rank correlation is also presented. The value distribution of the applicable objective function is generated. This distribution is analysed directly for central tendency, spread, skewness, and extreme values for the purposes of risk analysis. Risk analysis and business analytics are important areas in education and training for the information economy.

Author(S) Details

Dennis Ridley
School of Business and Industry, Florida A&M University, USA and Department of Scientific Computing, Florida State University, USA.

Felipe Llaugel
Universidad Autonoma de Santo Domingo, USA.

Inger Daniels
School of Business and Industry, Florida A&M University, USA.

Abdullah Khan
School of Business, Claflin University, USA.

View Book:- https://stm.bookpi.org/NRAMCS-V1/article/view/6559

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