c10_nlp_methods (1) - Instructions Chapter10

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Instructions Page 1 Chapter 10 Operations Research Models and Methods Paul A. Jensen and Jonathan F. Bard Nonlinear Programming Methods Instructions The prolems are solved with the Excel Solver. When the LP/IP Solver is used, that add-in must also be added. Sect. Nonlinear Programming Methods 1 Classical Optimization Add-ins Used The eight examples in the section plus the nonquadratic cases Teach NLP add-in 2 Equality Constraints Example solved with Math Programming add-in with Excel Solver Math Programming-Nonlinea Example solved with Teach NLP and Excel Solver Teach NLP/Excel Solver 3 Inequality Constraints Example solved with Teach NLP and Excel Solver Teach NLP/Excel Solver Example solved with Math Programming add-in with Excel Solver Math Programming-Nonlinea 4 Separable Programming Example solved with Math Programming add-in with Excel Solver Math Programming-Nonlinea http://www.me.utexas.edu/~jensen/ORMM/computation/unit/mp_add/index.html http://www.me.utexas.edu/~jensen/ORMM/methods/unit/nonlinear/subunits/teach_nlp/index.html To use this workbook, you must first load the Math Programming add-in. See the Excel help file  topic "About add-ins" before continuing. This workbook comes without control buttons. To make the buttons choose the Add Buttons  commands from  the Math Programming add-in. This adds buttons to all the worksheets. Ex_1_8 Ex_9 Ex_10 Ex_11 Ex_12 Ex_13
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Instructions Page 2 5 Quadratic Programming Example solved with Math Programming add-in with Excel Solver Math Programming-Nonlinea 7 Multidimensional Search Methods Example solved with Teach NLP using steepest descent (gradient search) Teach NLP Gradient Search on a more General Function (the location problem) Teach NLP Algorithms for Constrained Optimization (Supplement) Example solved with Math Programming add-in with Excel Solver Math Programming-Nonlinea Example solved with Math Programming add-in with Excel Solver Math Programming-Nonlinea Demonstration of the Teach NLP Add-in Examples for the section solved with Teach NLP Teach NLP Ex_14 Quad Location Ex_17 Ex_18 TeachNLP
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Instructions Page 3 ar/Excel Solver ar/Excel Solver ar/Excel Solver
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Instructions Page 4 ar/Excel Solver ar/Excel Solver ar/Excel Solver
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Example 1 x_e1 Values f_e1(x_e1) x_e1 c Q 1 x_e1* x_e1(1) 2.5 -25 1 -20 1 8 2.5 cx = -50 .5xQx= 25 x_e1 Solution Gradient Hessian DiagonalizeAnalysis 1 2.5 0 8 8 This is a stationary point (Gradient Norm =0). Objective -25 Var. Linear Tran The Hessian matrix is positive definite. It is a strong local minimum. 1
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This note was uploaded on 05/12/2011 for the course INDUSTRIAL 321 taught by Professor Memet during the Spring '11 term at Mitchell Technical Institute.

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c10_nlp_methods (1) - Instructions Chapter10

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