Minimax and Applications

Techniques and principles of minimax theory play a key role in many areas of research, including game theory, optimization, and computational complexity. In general, a minimax problem can be formulated as min max f(x, y) (1) ",EX !lEY where f(x, y) is a function defined on the product of X and Y spaces. There are two basic issues regarding minimax problems: The first issue concerns the establishment of sufficient and necessary conditions for equality minmaxf(x,y) = maxminf(x,y). (2) "'EX !lEY !lEY "'EX 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). (3) "'EX !lEY There are two developments in minimax theory that we would like to mention.

Report

` ... a valuable book carefully written in a clear and concise fashion. The survey papers give coherent and inspiring accounts ... coverage of algorithmic and applied topics ... is impressive. Both graduate students and researchers in fields such as optimization, computer science, production management, operations research and related areas will find this book to be an excellent source for learning about both classic and more recent developments in minimax and its applications. The editors are to be commended for their work in gathering these papers together.'
Journal of Global Optimization, 11 (1997)

Product details

• Assisted by: Panos Pardalos (Editor), Panos M. Pardalos (Editor), Ding-Zhu Du (Editor), Ding-Zhu Du (Editor), M Pardalos (Editor), M Pardalos (Editor), Ding-Zhu Du (Editor), Ding-Zh Du (Editor)
• Publisher: Springer, Berlin
• Content: Book
• Product form: Paperback / Softback
• Publication date: 17.10.2013
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematica
• EAN: 9781461335597
• ISBN: 978-1-4613-3559-7
• Pages: 296
• Illustrations: XIV, 296 p.
• Dimensions (packing): 16 x 24 cm
• Series: Nonconvex Optimization and Its Applications > .4; Nonconvex Optimization and Its Applications (closed) > .4; Nonconvex Optimization and Its Applications > 4
• Subjects: Algorithmen und Datenstrukturen, Algorithms, Optimization, Diskrete Mathematik, Mathematik für Informatiker, geometry, Networks, complexity, Scheduling, Programming, computation, Approximation, Gametheory, combinatorialoptimization