Cliff Ragsdale's Spreadsheet Modeling and Decision Analysis: A Practical PDF

By Cliff Ragsdale

ISBN-10: 0324656645

ISBN-13: 9780324656640

Cliff Ragsdale is an innovator of the spreadsheet educating revolution and is extremely looked within the box of administration technological know-how. The revised 5th version of SPREADSHEET MODELING AND choice research keeps the weather and philosophy that has made its previous variations such a success. New themes were further in addition to examples which are suitable to selection making in state-of-the-art enterprise global. This model of SPREADSHEET MODELING AND determination research has been up to date to be used with Microsoft place of work Excel 2007. It offers succinct guide within the most ordinarily used administration technology recommendations and exhibits how those instruments should be carried out utilizing the most up-tp-date model of Excel for home windows. this article additionally makes a speciality of constructing either algebraic and spreadsheet modeling talents.

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Read or Download Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Management Science, Revised (Book Only) PDF

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Extra info for Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Management Science, Revised (Book Only)

Example text

Another restriction Howie faces is that he has only 1,566 labor hours available during the next production cycle. Because each Aqua-Spa he builds (each unit of X1) requires 9 labor hours and each Hydro-Lux (each unit of X2) requires 6 labor hours, the constraint on the number of labor hours is stated as: 9X1 ϩ 6X2 ≤ 1,566 The General Form of an LP Model 23 The total number of labor hours used (represented by 9X1 ϩ 6X2) must be less than or equal to the total labor hours available, which is 1,566.

5. Identify any upper or lower bounds on the decision variables. Often, simple upper or lower bounds apply to the decision variables. You can view upper and lower bounds as additional constraints in the problem. In our example, there are simple lower bounds of zero on the variables X1 and X2 because it is impossible to produce a negative number of hot tubs. Therefore, the following two constraints also apply to this problem: X1 ≥ 0 X2 ≥ 0 Constraints like these are often referred to as nonnegativity conditions and are quite common in LP problems.

Xn) ≥ b An “equal to” constraint: f(X1, X2, . . , Xn) = b 20 Chapter 2 Introduction to Optimization and Linear Programming In each case, the constraint is some function of the decision variables that must be less than or equal to, greater than or equal to, or equal to some specific value (represented above by the letter b). We will refer to f(X1, X2, . . , Xn) as the left-hand-side (LHS) of the constraint and to b as the right-hand-side (RHS) value of the constraint. For example, we might use a “less than or equal to” constraint to ensure that the total labor used in producing a given number of products does not exceed the amount of available labor.

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Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Management Science, Revised (Book Only) by Cliff Ragsdale

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