Comparison of Contemporary Evolutionary Algorithms on the Rotated Klee-Minty Problem

The Rotated Klee-Minty Problem represents an advancement of the well-known linearly constrained Klee-Minty Problem that was introduced to illustrate the worst case running time of the Simplex algorithm. Keeping the linearity as well as the complexity of the original Klee-Minty Problem, the Rotated Klee-Minty Problem remedies potential biases with respect to Coordinate Search and turns out to be a suitable constrained test environment for randomized search heuristics. The present paper is concerned with the comparison of recent evolutionary algorithm variants for constrained optimization on this respective test bed. The considered algorithm variants include the most successful participants of the CEC Competition on Single Objective Real-parameter optimization and other selected strategies that are not directly applicable to the CEC test suite. Taking into account the diverse constraint handling approaches, the performance results of all search heuristics are interpreted. It turns out that most strategies that have been successful in the CEC competitions do have severe problems on the RKMP.