Application of imperialist competitive algorithm with its modified techniques for multi-objective optimal power flow problem: A comparative study

Application and Comparison of Metaheuristic and New Metamodel Based Global Optimization Methods to the Optimal Operation of Active Distribution Networks

“…These algorithms do not directly use the derivative information of the objective function during the search, illustrating high ability to locate the global optimum and to cope with large-scaled non-linear problems. Widely-used population-based global optimization methods include differential evolution (DE) [6,7], particle swarm optimization (PSO) [7], genetic algorithm (GA) [8], evolutionary programming (EP) [9,10], simulated annealing (SA) [11], gravitational search algorithm (GSA) [12,13], Tabu search algorithm (TS) [14], artificial bee colony algorithm (ABC) [15], modified imperialist competitive algorithm (MOMICA) [16], and black hole optimization algorithm. These global optimization search methods are capable of solving complex global optimization problems with mixed continuous and discrete variables, and discontinuous objective function.…”

Multi-objective optimization of orbit transfer trajectory using imperialist competitive algorithm

“…This algorithm has been applied in optimization problems in many engineering researches such as controller design [7], logic circuit optimization [8], power flow optimization [9] and virtual machine placement [10]. The only fair application of ICA in trajectory optimization of spacecraft has been presented by Shafieenejad et al [11] in which the optimal control problems in a low-thrust space orbit transfer problem is tackled using ICA with regard to path design viewpoint and free initial condition.…”

Improved symbiotic organisms search algorithm for solving unconstrained function optimization

“…ABC uses the foraging behavior of a honey bee, ACO implemented based on the searching behavior of ant from the source to the destination, and HS is related to the improvisation process of a musician. Some of the applications of these algorithms are given in references (Chander et al, 2011;Wang et al, 2012;Canelas et al, 2013;Hecker et al, 2014;Ghasemi et al, 2014;Li & He, 2014;Baykasoğlu et al, 2014;Nama et al, 2015;Rao, 2016;Bolañosa et al, 2015;Mohammadia et al, 2015;Bhunia et al, 2015;Hosseini et al, 2014;Aulady, 2013;Nama et al, 2016;Rao & Patel, 2014;Barati et al, 2016;Eshraghi, 2016;Rout et al, 2016;Mir & Rezaeian, 2016;Abido, 2016;Gen et al, 2016;Aickelin & Dowsland, 2014;Hecker et al, 2013).…”