[PDF] Top 20 Sensitivity analysis and uncertainty in linear programming

... of uncertainty. The use of SA to allay concerns about uncertainty draws attention to an issue that rarely arises in the development of LP ...under uncertainty, it is critical to prop- erly reflect the ... See full document

... risk analysis offers many significant advantages over a traditional probabilistic approaches because it provides convenient and comprehensive ways to handle several of the most practical se- rious problems face by ... See full document

... a linear programming formulation is ...grey linear programming (GLP) is a development of the classical linear programming which allows uncertainty to be effectively ... See full document

... In the sequel of this section, we give a brief overview of the existing metamodelling methods (Section 2.1), then we focus on a specific method: the reduced basis method, which will be presented, in the linear ... See full document

... Fuller [5] proposed that the solution to fuzzy linear programming problems with symmetrical triangular fuzzy numbers is stable with respect to small changes of centers of fuzzy numbers. Perturbations occur ... See full document

... known. There are two reasons that cause these uncertainties. First, the underlying mathematical model (i.e., GTD) is constructed on sim- plified hypothesis. Second, uncertainties are also attached to the values of the ... See full document

... for sensitivity analysis of dynamic ...of uncertainty analysis, we calculated confidence intervals that encapsulated true parameter values as well as the true expression of the genes in the ... See full document

... The random sampling codes available for nuclear engineering applications all have their peculiarities. XSUSA [48] can vary the elastic, (n,2n) and inelastic scattering, the capture and fis- sion cross section, nu-bar and ... See full document

... That some of the major problems faced by the constructors of the industrial sector in Iraq in non-optimal use of available resources as a result of not using scientific methods in planning and decision-making, resulting ... See full document

... Somewhat surprisingly, the calculated permafrost depth would be about 40 m less in the north. Intuitively, one would expect permafrost to reach greater depths in the north, be- cause of the inferred temperature gradient ... See full document

... integer linear programming (MILP) was applied as a modeling tool to a power generation scheduling problem of a major power producer in ...optimality analysis on the proposed model in [1] in order to ... See full document

... Predictive science which refers to the application of computational models to the study and the prediction of physical or engineering systems has emerged as a powerful and an indispensable tool for resolving scientific ... See full document

... The Morris method (Campolongo et al., 2007; Morris, 1991) is a sensitivity analysis method that is particularly well suited to a model with significant computational overburden, as is the case here. The ... See full document

... a linear programming model combined with sensitivity analysis based on discounted cash flow to determine the optimal financing mix of the project given governmental initial subsidy for ... See full document

... with uncertainty in water resources systems including fuzziness, subjectivity, imprecision and lack of adequate ...fuzzy linear programming model to a multipurpose single ...the uncertainty in ... See full document

... Keywords: SLEUTH model; Sensitivity Analysis; uncertainty assessment; urban expansion.. 34 35.[r] ... See full document

... of linear pro- gramming models must be well defined and pre- ...exists uncertainty about the pa- ...of linear programming problems may be represented as fuzzy ...fuzzy linear ... See full document

... Our objective in this paper is to study multiparametric sensitivity analysis for the linear sum-of-ratios fractional programming. For computational ease, we consider ob- jective function with ... See full document

... Linear programming is an analysis technique in which linear algebraic relationships represent a firm’s decisions given a business objective and resource constraints. Steps in applicati[r] ... See full document

... the uncertainty evaluation required, it is very important to analyze all the key components influ- encing measurement ...of uncertainty in measurement). During the uncertainty eval- uation both type ... See full document