Innovative fuel management schemes based on evolutionary algorithms (EAs) now form an integral part of design and operation for nuclear reactors. In the present study, Estimation of Distribution Algorithm (EDA) has been developed for light water reactors (LWRs) and as a case study EDA has been applied to optimize the core loading pattern of VVER X2 benchmark’s initial core. EDA belongs to class of EAs where the optimization solution evolves through progress of generations and in each generation sampling of best candidates of previous generation is done. The main objectives of this study is firstly to develop and test EDA to optimize core loading pattern (LP) for VVER type cores and secondly to generate new optimized LPs having same safety features but with improved fuel utilization with respect to reference benchmark case. The most suitable values for internal parameters for EDA like population size (N), percentage best candidates (M) and weighting factor ‘α’ were evaluated for reaching a reasonable optimized solution in computationally efficient way. During this study, a number of optimized initial core loading patterns were generated, where the target parameters and safety limits are met. A comprehensive analysis for selected LPs has been carried out for full cycle and a comparison has been done for the reported safety and operational characteristics. It is observed that a few of the optimized LPs have better fuel economy than the benchmark LP.