3 papers
cs.NE2018
A Linear Constrained Optimization Benchmark For Probabilistic Search Algorithms: The Rotated Klee-Minty Problem
Michael Hellwig, Hans-Georg Beyer
The development, assessment, and comparison of randomized search algorithms heavily rely on benchmarking. Regarding the domain of constrained optimization, the number of currently…
cs.NE2018
A Covariance Matrix Self-Adaptation Evolution Strategy for Optimization under Linear Constraints
Patrick Spettel, Hans-Georg Beyer, Michael Hellwig
This paper addresses the development of a covariance matrix self-adaptation evolution strategy (CMSA-ES) for solving optimization problems with linear constraints. The proposed alg…
cs.NE2018
Benchmarking Evolutionary Algorithms For Single Objective Real-valued Constrained Optimization - A Critical Review
Michael Hellwig, Hans-Georg Beyer
Benchmarking plays an important role in the development of novel search algorithms as well as for the assessment and comparison of contemporary algorithmic ideas. This paper presen…