We can't find the internet
Attempting to reconnect
Something went wrong
Hang in there while we get back on track
£108.00
Springer Minimax and Applications: 4 - Nonconvex Optimization
Price data last checked 67 day(s) ago - refreshing...
We'll watch every seller, every day. One email when your price arrives.
This is the most expensive it has ever been. Walk away.
£108 today · previous high £108 · all-time low £106
NEW HERE?
Amazon shows you one price. We show you all of them.
Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.
WHAT'S ON THIS PAGE
when this has been cheap or pricey
where the price is heading next
all-time high & low, recent range
name your number, we'll email you
Price History & Forecast
Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.
Last 24 days · 24 data points (no recent data)
Price Distribution
Price distribution over 24 days • 2 price levels
Price Analysis
Most common price: £106 (16 days, 66.7%)
Price range: £106 - £108
Price levels: 2 different prices over 24 days
Description
Key Features
Explores core minimax theory and its role in game theory and computational complexity research.
Covers the mathematical formulation of minimax problems using X and Y spaces.
Provides insight into the conditions required for min-max and max-min equality.
Includes information on the classical minimax theorem of von Neumann.
Discusses duality theory as it relates to linear optimization problems.
Part of the Nonconvex Optimization and Its Applications series from Springer.
Product Specifications
- Brand
- Springer
- Format
- paperback
- ASIN
- 1461335590
- Domain
- Amazon UK
- Release Date
- 14 October 2011
- Listed Since
- 20 September 2013
Barcode
No barcode data available
Similar Products You Might Like
Maxima and Minima with Applications: Practical Optimization and Duality: 51 (Wiley Series in Discrete Mathematics and Optimization)
Wiley
Bi-Level Strategies in Semi-Infinite Programming: 71 (Nonconvex Optimization and Its Applications, 71)
Springer
Minimax Solutions in Sampling from Finite Populations: 64 (Lecture Notes in Statistics, 64)
Springer
Invitation to Linear Programming and Game Theory
Cambridge University Press
Handbook of Memetic Algorithms: 379 (Studies in Computational Intelligence, 379)
Springer
Handbook of Memetic Algorithms: 379 (Studies in Computational Intelligence, 379)
Springer
Submodular Functions and Optimization (Annals of Discrete Mathematics): Volume 58
Elsevier
MM Optimization Algorithms
Topics in Nonconvex Optimization: Theory and Applications: 50 (Nonconvex Optimization and Its Applications, 50)
Springer
Hybrid Metaheuristics: Powerful Tools for Optimization (Artificial Intelligence: Foundations, Theory, and Algorithms)
Springer
AlphaGo Simplified - Rule-Based AI and Deep Learning Book
Chapman and Hall/CRC
Interactive Fuzzy Optimization: 368 (Lecture Notes in Economics and Mathematical Systems, 368)
Springer
AlphaGo Simplified: Rule-Based AI and Deep Learning in Everyday Games
Chapman and Hall/CRC
Nonlinear Multiobjective Optimization: 12 (International Series in Operations Research & Management Science, 12)
Springer
Springer Mathematical Theory of Optimization: 56 - Book
Springer
Mathematical Optimization and Economic Analysis: 36 (Springer Optimization and Its Applications)
Springer
Interactive Decision Maps: Approximation and Visualization of Pareto Frontier: 89 (Applied Optimization, 89)
Springer
Mathematical Optimization and Economic Analysis: 36 (Springer Optimization and Its Applications, 36)
Springer
Springer Multi-Objective Memetic Algorithms - Studies in Comp Intel
Springer
Nonlinear Multiobjective Optimization: 12 (International Series in Operations Research & Management Science, 12)
Springer
Springer Multiple Criteria Optimization Annotated Survey 52
Springer
Geometric Problems on Maxima and Minima
Birkhauser
Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing: 21 (Wiley Series in Discrete Mathematics & Optimization)
Wiley
A Modern Approach to Teaching an Introduction to Optimization (Foundations and Trends® in Optimization)
Wiley