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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Minimax and Applications

Minimax and Applications

Ding-Zhu Du
Pardalos, Panos M.

Paperback

Series: Nonconvex Optimization and Its Applications, Book 4

CalculusGeneral Mathematics

ISBN10: 1461335590
ISBN13: 9781461335597
Publisher: Springer Pg
Published: Oct 14 2011
Pages: 296
Weight: 0.97
Height: 0.65 Width: 6.14 Depth: 9.21
Language: English
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.

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