Linear Programming History of linear programming goes back as far as 1940s. Main motivation for the need of linear programming goes back to the war time when they needed ways to solve many complex planning problems. The simplex method which is used to solve linear programming was developed by George B. Dantzig‚ in 1947. Dantzig‚ was one in who did a lot of work on linear programming‚ he was reconzied by several honours. Dantzig’s discovery was through his personal contribution‚ during WWII when Dantzig
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Describe the payout policy of Linear Technologies historically. Describe Linear’s current cash position and its financing needs. The company initiated its dividend in 1993 with a relatively conservative payout ratio of 15%‚ based on a quarterly dividend of $0.05/share/quarter ($0.00625 split adjusted as per Exhibit 3). As of 3Q2003‚ the dividend is also $0.05/share/quarter‚ adjusted for stock splits‚ which translates into a payout ratio of . The payout ratio is currently 27.5% on an as adjusted
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TO: Board of Directors‚ Linear Technologies FROM: Mr. Paul Coghlan CFO‚ Linear Technologies RE: Dividend Policy Summary: Based on the financials to date and the forward looking capital investments required Linear should increase their dividend payout by $0.01 per share. Entering the fourth quarter of 2003 the market seems to show continued signs of improvement. The company has shown steady growth and revenues are forecasted to exceed 2002’s by 19%. The forecast shows net income coming in
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Introduction Linear optimization is a mathematical method for determining a way to achieve the best outcome such as maximum profit or lowest cost in a given mathematical model for some list of requirements represented as linear relationships. Linear programming is a specific case of mathematical programming The Primary Purpose of the present investigation is to develop an interactive spreadsheet tool to aid in determining a maximum return function in 401K plan. In this paper‚ we discuss how the
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MULTIPLE REGRESSION After completing this chapter‚ you should be able to: understand model building using multiple regression analysis apply multiple regression analysis to business decision-making situations analyze and interpret the computer output for a multiple regression model test the significance of the independent variables in a multiple regression model use variable transformations to model nonlinear relationships recognize potential problems in multiple
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1. Qeach brand t=β0+β1*PMinute Maid t+β2*PTropicana t+β3*PPrivate label t+ueach brand t Q: quantity P: price By running the above regression model for each brand‚ we got the following elasticity matrix and the figures for “V” and “C.” Note that we used the average price and quantity for P and Q to calculate each brand’s elasticity. Price Elasticity | Tropicana | Minute Maid | Private Label | Tropicana | -3.4620441 | 0.40596537 | 0.392997566 | Minute Maid | 1.8023329 | -4.26820251 | 0.765331803
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Linear Functions There are three different ways to write linear functions. They are slope-intercept‚ point-slope‚ and standard form. There are certain situations where it is better to use one way than another to solve a problem. It is important to understand and comprehend the mechanics of these three forms so that you know what form to use when solving a problem. The first form‚ point-slope‚ is written as y-y1=m(x-x1). M is the slope and x1 and y1 correspond to a point on the line. It’s good to
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Linear Technology Linear Technology is a technology company that focuses on the different elements of semiconductors. The company mostly focuses on analog products within the semiconductor portion of the electronic industry. Linear Technology was unique in their payout policy in the sense that they started with announcing dividends and then continued onto repurchasing. Linear started dividends to gain the respect of investors as well as show that buying shares in the company of Linear was less
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An Introduction to Linear Programming Steven J. Miller∗ March 31‚ 2007 Mathematics Department Brown University 151 Thayer Street Providence‚ RI 02912 Abstract We describe Linear Programming‚ an important generalization of Linear Algebra. Linear Programming is used to successfully model numerous real world situations‚ ranging from scheduling airline routes to shipping oil from refineries to cities to finding inexpensive diets capable of meeting the minimum daily requirements. In many of these problems
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spreadsheet‚ next step is to use the Solver to find the solution. In the Solver‚ we need to identify the locations (cells) of objective function‚ decision variables‚ nature of the objective function (maximize/minimize) and constraints. Example One (Linear model): Investment Problem Our first example illustrates how to allocate money to different bonds to maximize the total return (Ragsdale 2011‚ p. 121). A trust office at the Blacksburg National Bank needs to determine how to invest $100‚000 in following
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