Tuning optimization algorithms for real-world problems by means of surrogate modeling.
Mike PreussGünter RudolphSimon WessingPublished in: GECCO (2010)
Keyphrases
- optimization problems
- real world
- combinatorial optimization
- optimization approaches
- discrete optimization
- convex optimization problems
- benchmark problems
- practical problems
- related problems
- optimization methods
- computational problems
- approximate solutions
- parameter tuning
- test problems
- wide range
- lower bound
- computationally efficient
- synthetic data
- tunable parameters
- objective function
- quadratic program
- evolutionary algorithm
- optimization procedure
- np complete
- mathematical programming
- theoretical analysis
- search methods
- metaheuristic
- evolution strategy
- significant improvement
- exact algorithms
- computational complexity
- data sets
- optimization criteria
- continuous optimization
- learning algorithm
- efficient algorithms for solving