Quadratic Programming with Computer Programs
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A01=Michael J. Best
Active Inequality Constraints
advanced quadratic programming techniques
Age Group_Uncategorized
Age Group_Uncategorized
algorithmic methods
Algorithms
Alternate Optimal Solutions
Author_Michael J. Best
automatic-update
Category1=Non-Fiction
Category=PBT
Category=PBWR
civil engineering applications
Cml
Complementary Slackness
convex analysis
COP=United States
Delivery_Delivery within 10-20 working days
Dual Feasibility
Dual Problem
Duality Theorem
Efficient Frontier
Efficient Portfolios
eq_isMigrated=2
eq_nobargain
Global Optimal Solution
Inefficient Frontier
Karush Kuhn Tucker Point
Language_English
Linear Equality Constraints
Linear Programming
Local Optimal Solution
mathematical optimization
Minimum Variance Portfolio
Nonconvex Quadratic Programming
operations research
Optimization
PA=Available
Portfolio Optimization Methods
Positive Semidefinite
Price_€50 to €100
PS=Active
QP
QP Algorithm
Quadratic Programming
Risk Free Asset
Risky Assets
softlaunch
statistical modeling
Strong Local Minimum
Unique Optimal Solution
Weak Duality Theorem
Product details
- ISBN 9781498735759
- Weight: 882g
- Dimensions: 178 x 254mm
- Publication Date: 18 Jan 2017
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
- Language: English
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Quadratic programming is a mathematical technique that allows for the optimization of a quadratic function in several variables. QP is a subset of Operations Research and is the next higher lever of sophistication than Linear Programming. It is a key mathematical tool in Portfolio Optimization and structural plasticity. This is useful in Civil Engineering as well as Statistics.
Michael J. Best is Professor Emeritus in the Department of Combinatorics and Optimization at the University of Waterloo. He is only the second person to receive a B.Math degree from the University of Waterloo and holds a PhD from UC-Berkeley. Michael is also the author of Portfolio Optimzation, published by CRC Press.
