PPT-Network Optimization Models

Chapter 10 Hillier and Lieberman Chapter 8 Decision Tools for Agribusiness Dr Hurleys AGB 328 Course Terms to Know Nodes Arcs Directed Arc Undirected Arc Links Directed Network Undirected Network Path Directed Path Undirected Path Cycle Connected Connected Network Tree Spanning Tree Arc Capacity Supply Node Demand Node Transshipment Node Sink Source Residual Network Residual Capacity Augmenting Path Cut Cut Value MaxFlow MinCut Theorem Feasible Solutions Property Integer Solutions Property Reverse Arc Basic Arcs . Rajmohan Rajaraman. Northeastern University, Boston. May 2012. Chennai Network Optimization Workshop. The Randomization Repertoire. 1. Randomization in Network Optimization. Very important toolkit:. Often simple routines yielding the best known approximations to hard optimization problems. Rajmohan Rajaraman. Northeastern University, Boston. May 2012. Chennai Network Optimization Workshop. Rumors and Routes. 1. Outline. Rumor spreading. Bounds on cover time. Small-world networks. Low-degree low-diameter models. TVCG 2013. Sungkil. Lee, Mike Sips, and Hans-Peter Seidel. Introduction. Class Visibility. Optimization . Example. Conclusion. Outline. Principles of effective color palettes (Trumbo, 1981) . Order: colors chosen to present an ordered statistical variables should be perceived as preserving that order. . . Kwangsoo. Han, Andrew B. Kahng, . Jongpil. Lee, . Jiajia Li. and Siddhartha Nath. VLSI CAD LABORATORY, . UC. San Diego. Outline. Motivation. Related Work. Our Optimization Framework. Experimental Setup and Results. Jonathan Hollingshead. Terms used in this presentation. Web page or page – a single document . on the Internet, typically with a single topic. Web site or site – a collection of individual web pages interconnected by hyperlinks. multilinear. gradient elution in HPLC with Microsoft Excel Macros. Aristotle University of Thessaloniki. A. . Department of Chemistry, Aristotle University of . Thessaloniki. B. Department of Chemical Engineering, Aristotle University of Thessaloniki. Qifeng. Chen. Stanford University. Vladlen. . Koltun. Intel Labs. Optical flow. Motion field between two image frames. Optical flow. Motion field between two image frames. Image 1. Image 2. optical flow. Introduction. In many complex optimization problems, the objective and/or the constraints are . nonlinear functions . of the decision variables. Such optimization problems are called . nonlinear programming . Introduction. In many complex optimization problems, the objective and/or the constraints are . nonlinear functions . of the decision variables. Such optimization problems are called . nonlinear programming . Introduction. Many important optimization models have a natural graphical network representation. . In this . chapter, we discuss some specific examples of network models. There are several . reasons for . Classification of algorithms. The DIRECT algorithm. Divided rectangles. Exploration and Exploitation as bi-objective optimization. Application to High Speed Civil Transport. Global optimization issues. Non-convex optimization. All loss-functions that are not convex: not very informative.. Global optimality: too strong. Weaker notions of optimality?. What is a saddle point?. Different kinds of critical/stationary points. Parameter estimation, gait synthesis, and experiment design. Sam Burden, Shankar . Sastry. , and Robert Full. Optimization provides unified framework. 2. ?. ?. ?. ?. ?. Blickhan. & Full 1993. Srinivasan. Puzhavakath. Narayanan, Vikas Varma, Swaminathan S, Krishna Moorthy. Presenters: Shankaranarayanan . Puzhavakath. Narayanan & Krishna Moorthy. OOF: Overview & Hands-on Session. October 14, 2020.