TOPIC – LINEAR PROGRAMMING Linear Programming is a mathematical procedure for determining optimal allocation of scarce resources. Requirements of Linear Programming • all problems seek to maximize or minimize some quantity • The presence of restrictions or constraints • There must be alternative courses of action • The objective and constraints in linear programming must be expressed in terms of linear equations or inequalities Objective
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Always start with scatter plot to see if the data is linear (i.e. if the relationship between y and x is linear). Next perform residual analysis and test for violation of assumptions. (Let y = arterial oxygen and x = blood flow). twoway (scatter y x) (lfit y x) regress y x rvpplot x 2. Since regression diagnostics failed‚ we transform our data. Ratio transformation was used to generate the dependent variable and reciprocal transformation was used to generate the independent variable. 3
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OBJECTIVES The objective of the experiment was To calibrate a 10 mL volumetric pipette To calibrate a 25 mL volumetric pipette To calibrate a 100 mL volumetric flask To calibrate a 50 mL measuring cylinder INTRODUCTION The purpose of this experiment is to study the relationship of several types of volumetric glassware and the accuracy of measuring the volumes of liquids very precisely in quantitative laboratory work. The accuracy of the measurement the volumes is the degree of closeness
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(2003) 1 OPERATIONS RESEARCH: 343 1. LINEAR PROGRAMMING 2. INTEGER PROGRAMMING 3. GAMES Books: Ð3Ñ IntroÞ to OR ÐF.Hillier & J. LiebermanÑ; Ð33Ñ OR ÐH. TahaÑ; Ð333Ñ IntroÞ to Mathematical Prog ÐF.Hillier & J. LiebermanÑ; Ð3@Ñ IntroÞ to OR ÐJ.Eckert & M. KupferschmidÑÞ LP (2003) 2 LINEAR PROGRAMMING (LP) LP is an optimal decision making tool in which the objective is a linear function and the constraints on the decision problem are linear equalities and inequalities. It is a very popular
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Table Z: Areas under the standard normal curve (negative Z) Second decimal place in z 0.06 0.05 0.04 0.03 0.09 0.08 0.07 0.02 0.01 0.0001 0.0001 0.0002 0.0002 0.00 * 0.0000 0.0001 0.0001 0.0002 0.0002 z -3.9 -3.8 -3.7 -3.6 -3.5 0.0001 0.0001 0.0001 0.0002 0.0001 0.0001 0.0001 0.0002 0.0001 0.0001 0.0001 0.0002 0.0001 0.0001 0.0001 0.0002 0.0001 0.0001 0.0001 0.0002 0.0001 0.0001 0.0001 0.0002 0.0001 0.0001 0.0001 0
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Linear Programming Tools and Approximation Algorithms for Combinatorial Optimization by David Alexander Griffith Pritchard A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Combinatorics and Optimization Waterloo‚ Ontario‚ Canada‚ 2009 c David Alexander Griffith Pritchard 2009 I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis‚ including any required final revisions
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Chapter 8 Linear Programming Applications To accompany Quantitative Analysis for Management‚ Eleventh Edition‚ Global Edition by Render‚ Stair‚ and Hanna Power Point slides created by Brian Peterson Copyright © 2012 Pearson Education 8-1 Learning Objectives After completing this chapter‚ students will be able to: 1. Model a wide variety of medium to large LP problems. 2. Understand major application areas‚ including marketing‚ production‚ labor scheduling‚ fuel blending‚ transportation‚ and
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S-curve describes how the performance or cost characteristics of a technology change with time and continued investments. While the horizontal axis shows the history (time and investment) of technical innovations‚ the vertical axis shows some problems of product performance or cost competitiveness. The pace of improvement slows when the established technology is improved and approaching its maturity. Many problems which a new technology has to face with are solved over time and with investment
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5 5 5 Compute: ATB(3 marks) tr (AB)(1 mark) (e) Determine if (2‚ -1) is in the set generated by = (3‚ 1)‚ (2‚ 2) (5 marks) Question Two (20 marks) Let T: R2 R2 be defined by T(x‚ y) = (x + y‚ x). Show that T is a linear transformation.(7 marks) Find the basis and dimension of the row space of the matrix.(6 marks) 2 -1 3 A= 1 1 5 -1 2 2 Compute A-1 using row reduction method.(7 marks) 1 4 3 A= -1 -2 0 2
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of period “zero”. So the first “future” cash flow accrues at time ..... We use the letter “t” to refer to a “generic” period. “now” “in one year” “in two years” 0 1 2 CF0 CF1 CF2 APR: Annual Percentage Rate. EAR: Expected A Rate. For simplicity‚ we will assume that all cash flows accrue at the very end of a “period”. That is unrealistic‚ but it simplifies things a bit. Easy to adapt calculations where needed (using spreadsheets) Some asset pricing tools
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