'Optimality conditions' presentation slideshows

Optimality conditions for constrained optimisation

Optimality conditions for constrained optimisation. Recall: Optimisation conditions for unconstrained problem with one variable function. One variable function:. Recall: Optimisation conditions for unconstrained problem with several variables function. Several variables function:.

1.6k views • 159 slides

(Nonlinear) Multiobjective Optimization

(Nonlinear) Multiobjective Optimization. Kaisa Miettinen miettine@hse.fi Helsinki School of Economics http://www.mit.jyu.fi/miettine/. Motivation. Optimization is important Not only what-if analysis or trying a few solutions and selecting the best of them

1.38k views • 115 slides

Minimum cost flows: Introduction and basic algorithms

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Outline

Outline. LP formulation of minimal cost flow problem useful results from shortest path problem optimality condition residual network potentials of nodes reduced costs of arcs (with respect to a given set of potentials) the optimality conditions for networks

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Outline

Outline. relationship among topics secrets LP with upper bounds by Simplex method basic feasible solution ( BFS ) by Simplex method for bounded variables extended basic feasible solution ( EBFS ) optimality conditions for bounded variables ideas of the proof examples

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15.082J and 6.855J and ESD.78J November 30, 2010

15.082J and 6.855J and ESD.78J November 30, 2010. The Multicommodity Flow Problem. Lecture overview. Notation A small illustrative example Some applications of multicommodity flows Optimality conditions A Lagrangian relaxation algorithm. = cost of sending 1 unit of commodity k in (i,j).

563 views • 34 slides

15.082J and 6.855J and ESD.78J November 30, 2010

15.082J and 6.855J and ESD.78J November 30, 2010. The Multicommodity Flow Problem. Lecture overview. Notation A small illustrative example Some applications of multicommodity flows Optimality conditions A Lagrangian relaxation algorithm. = cost of sending 1 unit of commodity k in (i,j).

345 views • 34 slides

Minimum Cost Flows

Minimum Cost Flows. CONTENTS Introduction to Minimum Cost Flows (Section 9.1) Applications of Minimum Cost Flows (Section 9.2) Structure of the Basis (Section 11.11) Optimality Conditions (Section 9.3) Obtaining Primal and Dual Solutions (Section 11.4)

564 views • 33 slides

Class 21

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Timing-Driven Routing for FPGAs Based on Lagrangian Relaxation

Timing-Driven Routing for FPGAs Based on Lagrangian Relaxation. Seokjin Lee * , D. F. Wong + * Dept. of Electrical and Computer Engineering + Dept. of Computer Sciences The University of Texas at Austin. Outline. Overview Introduction FPGA Architecture, Routing resources

584 views • 26 slides

Nonlinear Programming in Price Optimization

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ECON 4925 Autumn 2007 Electricity Economics Lecture 10

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Local and Global Optima

Local and Global Optima. Which one is the real maximum?. f(x). A. D. x. Which one is the real optimum?. x 2. A. D. x 1. B. C. Local and Global Optima. The optimality conditions are local conditions They do not compare separate optima

575 views • 16 slides

ISM 206 Lecture 4

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AAE 320 Exam # 1 Review

AAE 320 Exam # 1 Review. Paul D. Mitchell. Goal. Explain what to expect for exam Overview topics on exam Give idea of how to study. What to Expect. Organization & format similar to previous exams Mostly problems that test your knowledge of major concepts

285 views • 13 slides

CS5 3 21 Numerical Optimization

CS5 3 21 Numerical Optimization. 14 Linear Programming: The Interior Point Method. Interior point methods for LP. There are many variations of IPM for LP Primal IPM, dual IPM, primal-dual IPM Potential Reduction Methods Path Following Methods Short-step methods Long-step methods

137 views • 12 slides

Support Vector Regression

524 views • 11 slides

SCED Security Constrained Economic Dispatch

SCED Security Constrained Economic Dispatch. Linear vs. Quadratic Programming Model.

292 views • 8 slides