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Unformatted text preview: BUS 660 – lecture aid Optimization Modeling Applications Introduction This module is an extension of the Module 6 introduction to optimization modeling. As discussed last week, linear optimization techniques are used to solve a wide array of optimization problems. Understanding the theory and concepts behind linear programming requires relatively complex mathematical reasoning. Yet, as found in Module 6, the Solver capability of ExcelÂ© can be used to set up and solve linear optimization problems more easily as compared with solving the problems graphically or algebraically. What is a Linear Optimization Model? As discussed last week and as found in the Module 6 homework problems, a linear optimization model consists of: 1) Variables- whose values are to be determined. 2) Constraints- that those variables are under. 3) An objective function- that is a linear combination of the variables and represents a measure (such as profit, cost, resources, etc.) that is being optimized. Note that the word optimize is to be interpreted as profit, cost, resources, etc....
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This note was uploaded on 08/05/2010 for the course BUS BUS-660 taught by Professor Sheilad.fournier-bonilla during the Spring '10 term at Grand Canyon.
- Spring '10