SY 2011-2012 Ms. derpina derp TABLE OF CONTENTS TITLE PAGE ACKNOWLEDGEMENT ii TOPICS Simple Discount 1 Simple Interest 2 Four types of Interest available 3 Compounded Amount and Compound Interest 4 Linear Programming Problems * Maximization 6 * Minimization 8 Forecasting by Trend Projection 10 Acknowledgement I would like to thank God for guiding and giving me motivation to do this math research paper; my friends for answering
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Del Cauca‚ Colombia.” TIMS Studies in the Management Sciences 17‚ 331-359. Hogan‚ K.‚ and C. ReVelle (1986). "Concepts and Applications of Backup Coverage." Management Science 32‚ 1434-1444. Plane‚ D. R.‚ and T.E. Hendrick (1974). “Mathematical programming and the location of fire companies for the Denver fire department‚” Management Scinec Report Series‚ University of Colorado‚ Bolder‚ Colorado. (also published in Operations Research). Roth‚ R. (1969). "Computer Solutions to Minimum-Cover Problems
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IMSE2008 Operational Research Techniques Problem Set: Linear Programming Due: Monday‚ October 20‚ 2014 Please submit to the general office of the IMSE department (Ms Kate Lee HW8-17) on Oct 20 Late submission will be discounted by 20% on a daily basis Please e-mail me msong@hku.hk if you have any questions Problem 1. Work through the simplex method step by step to demonstrate that the following problem is unbounded. (5 marks) max 5x1 + x2 + 3x3 + 4x4 s.t. x1 – 2x2 + 4x3
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S.) Elton Mayo (U.S) & L.H.C Tippett (England) 1940s - Multidisciplinary team approaches to complex system problems Simplex method of linear programming Operations research groups (England) and George B. Dantzig (U.S.) 1950-60s - Extensive development of operations research tools Simulation‚ waiting-line theory‚ decision theory‚ mathematical programming‚ project Many researchers in the U.S. and Western Europe
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Lecture 6 GOAL PROGRAMMING INTRODUCTION In many important real-world decision-making situations‚ it may not be feasible‚ or desirable to reduce all the goals of an organization into b. single objective. For example‚ instead of focusing only on optimizing profits‚ the organization may simultaneously be interested in maintaining a stable work force‚ increasing its share of market and limiting price increases. Goal programming is an extension of linear or nonlinear programming involving an objective
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that any content on such websites is‚ or will remain‚ accurate or appropriate. For Anna‚ Nicholas‚ and Nora Dani¨l and Margriet e Contents Preface 1 Introduction 1.1 Mathematical optimization . . . . . . 1.2 Least-squares and linear programming 1.3 Convex optimization . . . . . . . . . . 1.4 Nonlinear optimization . . . . . . . . 1.5 Outline . . . . . . . .
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Chapter 4 Linear Programming Applications in Marketing‚ Finance and Operations Management Learning Objectives 1. Learn about applications of linear programming that have been encountered in practice. 2. Develop an appreciation for the diversity of problems that can be modeled as linear programs. 3. Obtain practice and experience in formulating realistic linear programming models. 4. Understand linear programming applications such as:
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Applying Integer Linear Programming to the Fleet Assignment Problem ABARA American Airlines Decision Ti’chnohi^ics PO Box 619616 Dallasll’ort Worth Airport‚ Texas 75261-9616 We formulated and solved the fleet assignment problem as an integer linear programming model‚ permitting assignment of two or more fleets to a flight schedule simultaneously. The objective function can take a variety of forms including profit maximization‚ cost minimization‚ and the optimal utilization of a particular
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References: Bradley‚ S. P.‚ A. C. Hax‚ T. L. Magnanti. 1977. Applied Mathematical Programming. Addison-Wesley‚ Reading‚ MA. Hillier‚ F. S.‚ G. J. Lieberman. 2004. Introduction to Operations Research‚ 8th ed. McGraw Hill‚ Boston. Talluri‚ K.‚ G. van Ryzin. 2004. The Theory and Practice of Revenue Management. Kluwer‚ Boston. Tuck School of
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FORECASTING Managers are always trying to reduce uncertainty and make better estimates of what will happen in the future; this is the main purpose of forecasting. Some firms use subjective methods‚ seat-of-the pants methods‚ intuition‚ and experience. There are also several quantitative techniques‚ moving averages‚ exponential smoothing‚ trend projections‚ and least squares regression analysis. Eight steps to forecasting: * Determine the use of the forecast—what objective are we trying to
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