Primal and dual approximation algorithms for convex vector optimization problems.
Andreas LöhneBirgit RudloffFirdevs UlusPublished in: J. Glob. Optim. (2014)
Keyphrases
- approximation algorithms
- primal dual
- convex optimization problems
- optimization problems
- convex programming
- convex functions
- dual variables
- duality gap
- convex optimization
- np hard
- algorithm for linear programming
- dual formulation
- special case
- evolutionary algorithm
- minimum cost
- worst case
- cost function
- quadratic program
- vertex cover
- objective function
- metaheuristic
- set cover
- linear programming
- randomized algorithms
- combinatorial optimization
- network design problem
- np hardness
- facility location problem
- constant factor
- open shop
- constant factor approximation
- augmented lagrangian
- approximation ratio
- undirected graph
- convex hull
- approximation schemes
- precedence constraints
- convergence rate
- computational complexity
- disjoint paths
- lagrangian dual
- optimal solution
- genetic algorithm