Ideology algorithm: a socio inspired optimization methodology
This paper introduces a new socio inspired metaheuristic technique referred to as ideology algorithm (IA) It is inspired by the self interested and competitive behaviour of political party individuals which makes them improve their ranking. IA demonstrated superior performance as compared to other well known techniques in solving unconstrained test problems. Wilcoxon signed rank test is applied to verify the performance of IA in solving optimization problems. The results are compared with seven well known and some recently proposed optimization algorithms (PSO, CLPSO, CMAES, ABC, JDE, SADE and BSA) A total of 75 unconstrained benchmark problems are used to test the performance of IA up to 30 dimensions. The results from this study highlighted that the IA outperforms the other algorithms in terms of number function evaluations and computational time. The eminent observed features of the algorithm are also discussed.
Neural Computing and Applications