Designing the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm and Applying it to Substantially Improve the Efficiency of Multi-Objective Deformable Image Registration

The recently introduced Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) for discrete variables has been shown to be able to efficiently and effectively exploit the decomposability of optimization problems, especially in a grey-box setting, in which a solution can be efficiently updated after a modification of a subset of its variables....