Log-logistic SOMA with quadratic approximation crossover

Though population based algorithms performs well to solve many global optimization problems, many attempts has been made in literature to improve the efficiency of these algorithms. One possible way is to hybridized them with the features of other deterministic or population based techniques. This Paper presents a Log-LogisticSelf organizing migrating algorithm with quadratic approximation crossover (LLSOMAQI). This algorithm is an extension of algorithms SOMAQI, in which Self Organizing Migrating Algorithm (SOMA) has been hybridized with quadratic approximation (QA) crossover operator and SOMA-M, which is hybridization of SOMA and Log-Logistic (LL)mutation. LLSOMAQI has been tested on 15 benchmark unconstrained test problems and an analysis has been made between the three algorithms. LLSOMAQI, its originator SOMA and PSO to show the efficiency of this algorithm over other population based algorithms.