Title : 
Electromagnetic Optimization Using a Cultural Self-Organizing Migrating Algorithm Approach Based on Normative Knowledge
         
        
            Author : 
Coelho, Leandro Dos Santos ; Alotto, Piergiorgio
         
        
            Author_Institution : 
Autom. & Syst. Lab., Pontifical Catholic Univ. of Parana, Curitiba
         
        
        
        
        
            fDate : 
3/1/2009 12:00:00 AM
         
        
        
        
            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.
         
        
            Keywords : 
computational electromagnetics; evolutionary computation; optimisation; self-adjusting systems; solenoids; Loney´s solenoid design; cultural self-organizing migrating algorithm; electromagnetic optimization; modified SOMA approach; normative knowledge; operator; social environment; stochastic optimization algorithms; Cultural algorithm; Loney´s solenoid design; electromagnetic optimization; self-organizing migrating algorithm (SOMA);
         
        
        
            Journal_Title : 
Magnetics, IEEE Transactions on
         
        
        
        
        
            DOI : 
10.1109/TMAG.2009.2012668