Sensitivity analysis and uncertainty in linear programming article pdf available in interfaces 334. Pdf in the literature, sensitivity analysis of linear programming lp has been widely studied. Pdf positive sensitivity analysis psa is a sensitivity analysis method for linear. Sensitivity analysis the study of how changes in the coefficients of a linear programming problem affect the optimal solution sunk cost a cost that is not affected by the decision made. To remind you of it we repeat below the problem and our formulation of it.
Introduction integer linear programming ip played an important role is a problem solving and analysis tool. Often the parameter space to be investigated is enormous. Robust sensitivity analysis of the optimal value of linear programming guanglin xu samuel burery september 14, 2015 revised. Recall that in order to form ulate a problem as a linear program. As illustrations of particular duality rules, we use one small linear program made up for the purpose, and one from a game theory application that we previously developed.
Range of optimality answer the output states that the solution remains optimal as long as the objective function coefficient of x1 is between 7. Sensitivity analysis determines the effect on the optimal solution of changes in parameter values of the objective function and constraint equations. Complementary information and sensitivity analysis 1. The 100% rule is typically limited to changing only a few. The world is more complicated than the kinds of optimization problems that we are able to solve. Linear programming sensitivity analysis using solver. Sensitivity analysis 2 the term sensitivity analysis, sometimes also called postoptimality analysis, refers to an analysis of the effect on the optimal solution of changes in the parameters of problem on the current optimal solution. Subsequent results concern quantitative measures, in particular optimal value and solution point parameter derivative. The constraints could be related to the amount of money. However, the research on sensitivity analysis with functional relation has been sporadic and scattered. It will be incurred no matter what values the decision variables assume. Sensitivity analysis and uncertainty in linear programming. Most results are valid only under nondegeneracy assumption of optimal solutions and we refer to this study as classic sensitivity analysis.
In a linear programming problem, the binding constraints for the optimal solution are. Role of sensitivity analysis in linear programming. One approach to these questions is to solve lots of linear programming problems. Parametric nonlinear control problems subject to mixed controlstate. Sensitivity and stability analysis for nonlinear programming. The importance of sensitivity analysis in linear programming has been widely stressed in the management science literature. Pdf sensitivity analysis of linear programming in the presence of. Sensitivity analysis deals with finding out the amount by which we can change the input data for the output of our linear programming model to remain comparatively unchanged. Sensitivity analysis for nonlinear programming using penalty. Sensitivity analysis learning objectives what is sensitivity analysis. Under the circumstances of misleading optimal solutions the sensitivity analysis is applied to the linear programming. Sensitivity analysis and interpretation of solution. Imagine what would happen if the values of either c1 or c2 or both were to change. When b and c vary independently, the problem is known as a multi.
Analysis for linear programming finding the optimal solution to a linear programming mo del is imp ortan t, but it is not the only information a v ailable. This book covers all aspects of linear programming from the twodimensional lps and their extension to higher dimensional lps, through duality and sensitivity analysis and finally to. A linear programming model for the transportation problem is then used to show how a class of primal models gives rise to a certain class of dual models. This book covers all aspects of linear programming from the twodimensional lps and their extension to higher dimensional lps, through duality and sensitivity analysis and finally to the examination of commented software outputs. Linear programming sensitivity analysis self study quiz before taking the selftest, refer to the learning objectives at the beginning of the chapter, the notes in the margins, and the glossary at the end of the chapter. We propose a framework for sensitivity analysis of linear programs lps in. We give a brief overview of important results in several areas of sensitivity and stability analysis for nonlinear programming, focusing initially on qualitative characterizations e. Linear programming, sensitivity analysis and related. Pdf linear programming lp is one of the great successes to emerge from operations research and management science. In this section, i will describe the sensitivity analysis information provided. Computer solution and sensitivity analysis bit 2406 1 chapter topics computer solution sensitivity analysis bit 2406 2 simplex method the simplex method is a procedure involving a set of mathematical steps to solve linear programming problems.
Vanderbei october 17, 2007 operations research and financial engineering. Sensitivity analysis allows him to ask certain whatif questions about the problem. The following questions arise in connection with performing the sensitivity analysis. Pdf sensitivity analysis of linear programming in the. Linear programming by graphing, sensitivity analysis on. Linear programming, sensitivity analysis and related topics. Linear programming sensitivity analysis questions to be solved in class answer the questions in the space provided. Sensitivity analysis and interpretation of solution introduction to sensitivity analysis. Sa has shortcomings that run contrary to conventional wisdom.
Oct 16, 2015 after solving a linear programming problem by graphing, performing sensitivity analysis on the righthandside of a constraint and finding the range you are allowed to change the righthandside. Production and operations management, fall 2010, section b topic. However, only some very simple and special cases were considered when righthand side rhs parameters. Linear programming notes vii sensitivity analysis 1 introduction when you use a mathematical model to describe reality you must make approximations. November 4, 2015 abstract we propose a framework for sensitivity analysis of linear programs lps in minimization form, allowing for simultaneous perturbations in the objective coe cients and. Local perturbation analysis of linear programming with.
Kheirfam department of mathematics azarbaijan university of tarbiat moallem, tabriz, iran abstract in this paper. Sensitivity analysis helps to study how the optimal solution will change with changes in the input coefficients example a factory manufactures three products, which require three resources labour, material and administration. There are a number of questions that could be asked concerning the sensitivity of an optimal solution to changes in the data. Linearity assumptions usually are signi cant approximations. Since 20 is within this range, the optimal solution will not change. Chapter 7 sensitivity and parametric analysis robert j. Every commercial linear programming system provides this elementary sensitivity analysis, since the calculations are easy to. Cover linear programming, sensitivity analysis and related topics to my family, for their love and support contents preface acknowledgements introduction modelling using linear programming solving linear programmes linear programming. Pdf sensitivity analysis and uncertainty in linear programming. Operations researchsensitivity analysis wikibooks, open.
Sensitivity analysis of linear programming and quadratic programming algorithms for control allocation article pdf available april 2009 with 55 reads how we measure reads. The local solution is assumed to satisfy the second order. We discussed this topic when we talked about duality. In linear programming modal parameters are i objective function ii constraint coefficients 34172017 4. Bsa, we need an optimal basis associated with an optimal basic solution.
In this chapter we will address those that can be answered most easily. Positive sensitivity analysis psa is a sensitivity analysis method for linear programming that finds the range of perturbations within which positive value components of a given optimal solution. In this paper we establish a theoretical basis for utilizing a penaltyfunction method to estimate sensitivity information i. In the literature, sensitivity analysis of linear programming lp has been widely studied.
In the context of a purchase and sale of a business, a buyer or a sellers business broker will prepare a 1 to 3 year projection for a target that will contain significant assumptions such as product pricing, equipment utilization, direct cost percentages, levels of overhead, interest and tax rates. The porsche club of america sponsors driver education events that provide highperformance driving instruction on actual racetracks. Every commercial linearprogramming system provides this elementary sensitivity analysis, since the calculations are easy to. There is a tremendous amoun tof sensitivity information, or information ab out what happ ens when data v alues are c hanged. Changes may be reactions to anticipated uncertainties in the parameters or to new or changed information concerning the model. A sensitivity analysis typically entails changing the various assumptions in a financial model.
Applications include the calculation of con dence intervals and covariance matrices. Because safety is a primary consideration at such events, many owners elect to install roll bars. Linear programming sensitivity analysis self study quiz before taking the selftest, refer to the learning objectives at the beginning of the chapter, the notes. Methods such as linear sensitivity analysis or the global morris method can be used for screening out unimportant parameters before more complex global sensitivity methods are used. A set x 2 r is a convex set if given any two points x1. Costbenefit analysis benefit valuation discounting sensitivity analysis comparison costs benefits comparison costs health outcomes economic evaluation fiscal impact user fees government finance costeffectiveness analysis health impact discounting sensitivity analysis public project private project commercial appraisal. The approach of the book part i linear programming and sensitivity analysis. Nlp sensitivity analysis is of great practical interest for optimization practitioners. An area closely related to sa is interval linear programming ilp, which. Researchers have addressed a variety of important problems through integer linear programming. For the love of physics walter lewin may 16, 2011 duration. Advances in sensitivity analysis and parametic programming pp 57100 cite as. Snacks r us is deciding what to produce in the upcoming month. Strictly sensitivity analysis for linear programming problems.
One final observation on the state of the art in sensitivity analysis. Strictly sensitivity analysis for linear programming problems with upper bounds b. November 4, 2015 abstract we propose a framework for sensitivity analysis of linear programs lps in minimization form, allowing for. Postoptimal analyses, parametric programming, and related topics. Gal, postoptimal analysis, parametric programming and related topics mcgrawhill. Chapter 3 sensitivity analysis companion slides of applied mathematical programming by bradley, hax, and magnanti addisonwesley, 1977 prepared by. Pdf sensitivity analysis of linear programming and. Sensitivity analysis sensitivity is a postoptimality analysis of a linear program in which, some components of a, b, c may change after obtaining an optimalsolution with an optimal basis and an optimal objective value. Apr 17, 2017 definition of sensitivity analysispost optimality sensitivity analysis investigates the changes in the optimum solution resulting from changes in parameters of linear programming model. Ch 3 computer solution sensitivity analysis chapter 3. Sensitivity analysis in linear optimization optimization online. Sensitivity analysis and realtime control of parametric optimal.
Handbook for the economic analysis of health sector projects. Usually variation occurs in the rhs of the constraints and or the objective function coefficients. Finding the optimal solution to a linear programming model is important, but it is not the only information available. Linear programming sensitivity analysis using solver recall the production planning problem concerned with four variants of the same product which we formulated before as an lp. There are a few accepted techniques for changing several coefficients at once. Since this constraint is the linear programming, integer programming, sensitivity analysis, production planning 1. Sensitivity analysis, parametric programming, linear program, lexicographic. Gal, t postoptimal analyses, parametric programming and related topics. The local solution is assumed to satisfy the second. Sensitivity analysis 3 mit massachusetts institute of. After solving a linear programming problem by graphing, performing sensitivity analysis on the righthandside of a constraint and finding the range you are allowed to change the righthandside.
290 642 1225 532 619 312 1277 1091 936 346 751 1558 698 764 905 400 791 1291 884 799 79 786 1478 1466 698 680 1396 1592 6 1362 509 1405 312 695 1171 696 580 127 1332