Transcription of Introduction to Constrained Optimization
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Introduction to Constrained Optimization
Introduction to Constrained Optimization Overview Graphical OptimizationConstrained OptimizationIn the previous unit, most of the functions we examined were unconstrained, meaning they either had no boundaries, or the boundaries were soft. Constrained OptimizationIn the previous unit, most of the functions we examined were unconstrained, meaning they either had no boundaries, or the boundaries were soft. In this unit, we will be examining situations that involve constraint is a hard limit placed on the value of a variable, which prevents us from going forever in certain OptimizationWith nonlinear functions, the optimum values can either occur at the boundaries or between ininteriorMaximum atboundaryMaximum ininteriorMinimum atboundaryMaximum atboundaryMinimum ininteriorConstrained OptimizationWith
Enter the Objective Function After you have the feasible region and the corner points, it’s time to consider the objective function. x 1 x 2 (0, 0) (0, 10.8) (17, 0) (8, 6) The simplest way to optimize is to find the value of the objective function by plugging in each point, then choose the best one.
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