A linear constrained optimization benchmark for probabilistic search algorithms
Considering the domain of constrained optimization, the number of available benchmark environments bears no relation to the amount of distinct problem features. The rotated Klee-Minty problem represents the proposal of a scalable linear constrained optimization problem which is suitable for benchmarking Evolutionary Algorithms.
This repository provides a Matlab implementation of the benchmarking environment introduced in the paper: "A Linear Constrained Optimization Benchmark For Probabilistic Search Algorithms: The Rotated Klee-Minty Problem" by M. Hellwig and H.-G. Beyer, preprint available at \url{avialable soon}.
The reporting of implementation issues as well as suggestions for improvement (or modification) are welcome. Please contact hemi_at_fhv_dot_at