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Smooth, Unconstrained Nonlinear Optimization without Gradients

2. Hooke Jeeves or Pattern Search. Zero order No derivatives No line searches Works in discontinuous domain No proof of convergence Tool when other tools fails. References: Evolution and Optimum Seeking by Hans-Paul Schwefel Mark Johnson code handout. Characteristics. 3. Hooke Jeeves. With

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Smooth, Unconstrained Nonlinear Optimization without Gradients

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    1. 1 Smooth, Unconstrained Nonlinear Optimization without Gradients Hooke Jeeves 6/16/05

    2. 2 Hooke Jeeves or Pattern Search

    3. 3 Hooke Jeeves

    4. 4

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    6. 6 Hooke Jeeves Algorithm

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    11. 11 Lab Rerun the Spring_Start.desc file using Hooke_Jeeves with the default step size. Does it reach the same optimum? How many function calls did it take? Is this more or less efficient then Steepest Descent? On the next slide, label the X1 Step Size, X2 Step Size and algorithm step number next to each row for first 7 run counters.

    12. 12 Spring – Hooke Initial Steps

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