Selecting test problems from benchmark suites in constrained multiobjective optimisation

Benchmarking is essential to the effective conduct of algorithm development and selection. However, current benchmark suites in constrained multiobjective optimisation, consisting of constrained multiobjective optimisation problems (CMOPs), are lacking in many areas, particularly regarding their diversity and ability to differentiate among algorithms. This limits the ability to adequately conduct benchmarking in this domain. Despite the inadequacies of existing benchmark suites, there do exist CMOPs which are satisfactory according to certain criteria. This paper proposes a benchmark suite called the Selected Test Problems (STEP) suite. It is derived from a methodology for selecting the satisfactory CMOPs from the set of all CMOPs provided by the existing benchmark suites. The STEP suite is analysed in both the feature and performance spaces and is found to be diverse and able to distinguish among algorithms, in addition to other desirable characteristics.