CLUSTERED SELF ORGANISING MIGRATING ALGORITHM FOR THE QUADRATIC ASSIGNMENT PROBLEM
Donald David Davendra, Ivan Zelinka, Roman Šenkeřík, Abdul Halim Hakim, Pandian Vasant, Nader Nassif Barsoum · AIP conference proceedings · 2009
An approach of population dynamics and clustering for permutative problems is presented in this paper. Diversity indicators are created from solution ordering and its mapping is shown as an advantage for population control in metaheuristics. Self Organising Migrating Algorithm (SOMA) is modified using this approach and vetted with the Quadratic Assignment Problem (QAP). Extensive experimentation is conducted on benchmark problems in this area.