Open AccessSensitivity analysis of grey linear programming for optimisation problems
Author(s) -
Davood Darvishi,
Farid Pourofoghi,
Jeffrey YiLin Forrest
Publication year - 2021
Publication title -
badania operacyjne i decyzje/operations research and decisions
Language(s) - English
Resource type - Journals
eISSN - 2081-8858
pISSN - 1230-1868
DOI - 10.37190/ord210402
Subject(s) - linear programming , sensitivity (control systems) , mathematical optimization , range (aeronautics) , computer science , function (biology) , linear fractional programming , mathematics , algorithm , engineering , electronic engineering , evolutionary biology , biology , aerospace engineering
Sensitivity analysis of parameters is usually more important than the optimal solution when it comes to linear programming. Nevertheless, in the analysis of traditional sensitivities for a coefficient, a range of changes is found to maintain the optimal solution. These changes can be functional constraints in the coefficients, such as good values or technical coefficients, of the objective function. When real-world problems are highly inaccurate due to limited data and limited information, the method of grey systems is used to perform the needed optimisation. Several algorithms for solving grey linear programming have been developed to entertain involved inaccuracies in the model parameters; these methods are complex and require much computational time. In this paper, the sensitivity of a series of grey linear programming problems is analysed by using the definitions and operators of grey numbers. Also, uncertainties in parameters are preserved in the solutions obtained from the sensitivity analysis. To evaluate the efficiency and importance of the developed method, an applied numerical example is solved.