Electromagnetic Optimization Using a Cultural Self-Organizing Migrating Algorithm Approach Based on Normative Knowledge

Abstract

A new class of stochastic optimization algorithms called the self-organizing migrating algorithm (SOMA) has recently been proposed. SOMA works on a population of potential solutions called specimen and is based on the self-organizing behavior of groups of individuals in a ldquosocial environment.rdquo This paper introduces a modified SOMA approach based on an operator featuring normative knowledge, a characteristic of cultural algorithms. The efficiency of the proposed method is tested on Loney's solenoid design.