MOICA swMATH ID: 8963 Software Authors: Enayatifar, Rasul; Yousefi, Moslem; Abdullah, Abdul Hanan; Darus, Amer Nordin Description: MOICA: a novel multi-objective approach based on imperialist competitive algorithm A novel multi-objective evolutionary algorithm (MOEA) is developed based on imperialist competitive algorithm (ICA), a newly introduced evolutionary algorithm (EA). Fast non-dominated sorting and the Sigma method are employed for ranking the solutions. The algorithm is tested on six well-known test functions each of them incorporate a particular feature that may cause difficulty to MOEAs. The numerical results indicate that MOICA shows significantly higher efficiency in terms of accuracy and maintaining a diverse population of solutions when compared to the existing salient MOEAs, namely fast elitism non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO). Considering the computational time, the proposed algorithm is slightly faster than MOPSO and significantly outperforms NSGA-II. Homepage: http://www.google.de/#sclient=psy&hl=de&source=hp&q=MOICA Keywords: multi-objective imperialist competitive algorithm; multi-objective optimization; Pareto front Related Software: NSGA-II Cited in: 1 Document Standard Articles 1 Publication describing the Software, including 1 Publication in zbMATH Year MOICA: a novel multi-objective approach based on imperialist competitive algorithm. Zbl 1291.65174Enayatifar, Rasul; Yousefi, Moslem; Abdullah, Abdul Hanan; Darus, Amer Nordin 2013 Cited by 4 Authors 1 Abdullah, Abdul Hanan 1 Darus, Amer Nordin 1 Enayatifar, Rasul 1 Yousefi, Moslem Cited in 1 Serial 1 Applied Mathematics and Computation Cited in 2 Fields 1 Numerical analysis (65-XX) 1 Operations research, mathematical programming (90-XX) Citations by Year