Study of Different Boundary Constraint Handling Schemes in Interior Search Algorithm

Real-world problems usually have bounded search space and, therefore, the performance of optimization algorithms on them is also related to choose a proper boundary constraint handling methods. There are several classical approaches in the literature to handle the bounds. Usually, optimization algorithm use does not pay attentions to choose a proper boundary constraint handling scheme. In this study different boundary constraint handling schemes such as evolutionary scheme and classical schemes (including reflecting scheme, absorbing scheme, toroidal scheme, and random scheme) are evaluated on a recent evolutionary algorithm called interior search algorithm (ISA). In this paper, all the boundary constraint handling approaches have been adopted to ISA to solve a wide set of global numerical benchmark problems. The conclusions are made based on statistical results which clearly show the importance of different boundary constraint handlings in the searching process. The results obtained using the evolutionary boundary constraint handling scheme are better than the ones obtained by the other well-known approaches and it seems this scheme is suitable for a wider range of evolutionary optimization problems with very good convergence rate.