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du d minimax applications 1995

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Textbook in PDF format Techniques and principles of minimax theory play a key role in many areas of research, including game theory, optimization, and computational complexity. The classical minimax theorem of von Neumann is a result of this type. Duality theory in linear and convex quadratic programming interprets minimax theory in a different way. The second issue concerns the establishment of sufficient and necessary conditions for values of the variables x and y that achieve the global minimax function value f(x*, y*) = minmaxf(x, y). There are two developments in minimax theory that we would like to mention. Front Matter Minimax Theorems and Their Proofs A Survey on Minimax Trees And Associated Algorithms An Iterative Method for the Minimax Problem A Dual and Interior Point Approach to Solve Convex Min-Max Problems Determining the Performance Ratio of Algorithm Multifit for Scheduling A Study of On-Line Scheduling Two-Stage Shops Maxmin Formulation of the Apportionments of Seats to a Parliament On Shortest K -Edge Connected Steiner Networks with Rectilinear Distance Mutually Repellant Sampling Geometry and Local Optimality Conditions for Bilevel Programs with Quadratic Strictly Convex Lower Levels The Spherical One-Center Problem On Min-Max Optimization of a Collection of Classical Discrete Optimization Problems Heilbronn Problem for Six Points in a Planar Convex Body Heilbronn Problem for Seven Points in a Planar Convex Body On the Complexity of Min-Max Optimization Problems and their Approximation A Competitive Algorithm for the Counterfeit Coin Problem A Minimax αβ Relaxation for Global Optimization Minimax Problems in Combinatorial Optimization Back Matter

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Du D. Minimax and Applications 1995.pdf 22.5 MB

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du d minimax applications 1995

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