Abstract

This paper proposes a new variant of harmony search (HS) algorithm i.e. evolutionary harmony search (EHS), for exploiting in the loading pattern optimization (LPO) problem. The main innovations of EHS are the consideration of current best harmony vector in creating the new solution vector in any iteration and applying a pitch adjustment approach using a mutation strategy borrowed from the realm of the differential evolution (DE) algorithms, both with dynamic probabilities. Reactor core pattern optimization has been done using EHS for two test cases including KWU PWR and VVER-440. In order to represent the EHS capability to gain improved results in the LPO problem, a comparison is performed between results of EHS and a recent developed HS algorithm i.e. self-adaptive global best harmony search (SGHS). Numerical results show a major and distinctive enhancement of the proposed approach, EHS, in obtaining convergent results in comparison to SGHS approach. As a result, I can recommend the checking of EHS performance in other optimization problems.

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