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L23 Numerical Methods part 3
Project Homework Review Steepest Descent Algorithm Summary Test 4 results
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H22 ans optimum solution __0.444___ min value __0.0494__
interval of uncertainty__0.889__ number of fcn evals __6____
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H22 cont’d For iterations # 2 on….The interval is reduced to 0.888/1.333 =67% …. For the cost of 2 function evaluations. If we create a measure of efficiency
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H22
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H22 optimum solution __.472____ min value __.0124______
interval of uncertainty___0.764_____ number of fcn evals ___5_____ For iterations # 2 on….The interval is reduced to 61.8% of interval, I for the cost of only 1 function evaluation. If we create a measure of efficiency Golden Section Best
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Search algorithm? 1. Find a direction, then
2. Find best step size for alpha 3. Repeat steps 1 and 2 ‘til “done”
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Unimodal functions in “locale”
monotonic decreasing then monotonic increasing monotonic increasing then monotonic decreasing Figure 10.4 Unimodal function f().
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Review: Step Size Methods
“Analytical” Search direction = (-) gradient, (i.e. line search) Find f’(α)=0, f’’(α)≥0 Region Elimination (“interval reducing”) Equal interval Alternate equal interval Golden Section Others Newton-Raphson Successive quadratic Interpolation
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Successive Alternate Equal Interval
Assume bounding phase has found Min can be on either side of Point values… not a line But for sure its not in this region!
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Golden section Figure 10.9 Graphic of a section partition.
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Descent Algorithm? Descent is guaranteed!
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Steepest descent algorithm
How does it work?
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“Modified” Steepest-Descent Algorithm
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Ex 10.4 Use Solver to find α*
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EX 10.4 ||c||=0 Done!
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H22 Prob 10.52 Let’s use SteepDescentTemplate.xls to set up and solve.
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Summary Step size methods: analytical, region elimin.
Golden Section is very efficient Algorithms include stopping criteria (||c||,∆f ) Steepest descent algorithm Convergence is assured Lots of Fcn evals (in line search) Each iteration is independent of previous moves (i.e. totally “local” ) Successive iterations slow down.. may stall
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