PPT-Chapter 3 Linear Programming: Sensitivity Analysis

and Interpretation of Solution Introduction to Sensitivity Analysis Graphical Sensitivity Analysis Sensitivity Analysis Computer Solution Limitations of Classical Sensitivity Analysis In the previous chapter we discussed. 1. 3.3 Implementation. (1) naive implementation. (2) revised simplex method. (3) full tableau implementation. (1) Naive implementation :. Given basis . . Compute . ( solve . ). Choose . such that . Jake Blanchard. Fall . 2010. Introduction. Sensitivity Analysis = the study of how uncertainty in the output of a model can be apportioned to different input parameters. Local sensitivity = focus on sensitivity at a particular set of input parameters, usually using gradients or partial derivatives. 1. Sensitivity Analysis. Basic theory. Understanding optimum solution. Sensitivity analysis. Summer 2013. LP: Sensitivity Analysis. 2. Introduction to Sensitivity Analysis. Sensitivity analysis . means determining effects of changes in parameters on the solution. It is also called What if analysis, Parametric analysis, Post optimality analysis, etc,. It is not restricted to LP problems. Here is an example using Data Table.. Thorsten Wagener. thorsten.wagener@bristol.ac.uk. With Francesca . Pianosi. Francesca.pianosi. @bristol.ac.uk. My background. Civil engineering with focus on hydrology. University of Siegen, TU Delft, Imperial College London. Thorsten Wagener. thorsten.wagener@bristol.ac.uk. With Francesca . Pianosi. Francesca.pianosi. @bristol.ac.uk. My background. Civil engineering with focus on hydrology. University of Siegen, TU Delft, Imperial College London. Introduction to Linear Programming. Introduction. Linear programming. Programming means planning. Model contains linear mathematical functions . An application of linear programming. Allocating limited resources among competing activities in the best possible way. McGraw-Hill/Irwin. Operations Management, Eighth Edition, by William J. Stevenson. Copyright © 2005 by The McGraw-Hill Companies, Inc. All rights reserved.. Used to obtain optimal solutions to problems that involve restrictions or limitations, such as:. Sensitivity Analysis. Sensitivity Analysis. What if there is uncertainly about one or more values in the LP model?. Raw material changes,. Product demand changes, . Stock price. Sensitivity analysis allows a manager to ask certain hypothetical questions about the problem, such as: . Ref. Book:- Wood Power Generation, Operation, and Control - Allen J. Wood, Bruce F. . Wollenberg. An Overview of Security Analysis. Study the power system with approximate but very fast algorithms.. Select only the important cases for detailed analysis.. Rolf Langland. Data Assimilation Section. Naval Research Laboratory. Monterey, CA . langland@nrlmry.navy.mil. Including . Material Provided by. Dr. Ronald M. Errico (NASA-UMBC). Santa . Fe, N.M., . 31 July . Objective. The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established. . We conduct a variance-based sensitivity analysis . of hemispheric sea ice properties to 39 input parameters. The method accounts for non-linear and non-additive effects in the model.. Spring . 2018. Sungsoo. Park. Linear Programming 2018. 2. Instructor . Sungsoo. Park (room 4112, . sspark@kaist.ac.kr. , . tel:3121. ). Office hour: Mon, Wed 14:30 – 16:30 or by appointment. Classroom: E2-2 room 1120. understand and implement editorial opportunities and stunts across syndicated channels Monitor competitive programming and marketplace trends and analyze their implications Fall . 2010. Introduction. Sensitivity Analysis = the study of how uncertainty in the output of a model can be apportioned to different input parameters. Local sensitivity = focus on sensitivity at a particular set of input parameters, usually using gradients or partial derivatives.