Duality in Optimization and Variational Inequalities
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A01=C.j. Goh
advanced duality theory applications
Author_C.j. Goh
Auxiliary Function
Basic Feasible Solution
Category=UB
Closed Convex Cone
computational optimisation methods
convex
convex analysis
Cotree Arc
Dual Feasibility
Dual LP
Duality Gap
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Feasible Flow
function
functions
gap
Gap Function
lagrangian
Lagrangian Dual
Linear System
MATHEMATICAL PRELIMINARIES
mathematical programming
multicriteria
Multicriteria Optimization
Multicriteria Optimization Problem
network flow theory
Node Arc Incidence Matrix
Nonbasic Variable
nonconvex optimisation
optimality conditions
problem
Problem VI
Problem VVI
problems
Scalar VI
strong
Variational Inequalities
VE
Vector Variational Inequalities
weak
Weak Duality
Weak Vector Equilibrium
WVVI
Product details
- ISBN 9780367396152
- Weight: 610g
- Dimensions: 178 x 254mm
- Publication Date: 10 Oct 2019
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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This comprehensive volume covers a wide range of duality topics ranging from simple ideas in network flows to complex issues in non-convex optimization and multicriteria problems. In addition, it examines duality in the context of variational inequalities and vector variational inequalities, as generalizations to optimization. Duality in Optimization and Variational Inequalities is intended for researchers and practitioners of optimization with the aim of enhancing their understanding of duality. It provides a wider appreciation of optimality conditions in various scenarios and under different assumptions. It will enable the reader to use duality to devise more effective computational methods, and to aid more meaningful interpretation of optimization and variational inequality problems.
Goh, C.j.
