Algorithms are used to optimize both single and multi-objective system limits. This research aimed to detect the …. The research uses binary particle swarm optimization and shuffled frog leap (BPSO-SLFA) algorithms for simulation and … testing of an optimal power flow (OPF) on 33 and 69 bus radial distribution system. The result shows that the algorithms give …

performed utilizing a multi-objective evolutionary algorithm on a sample of S&P 100 constituents. Our optimization procedure …

-of-the-art multi-objective evolutionary algorithms and demonstrate the effectiveness of our proposed algorithm. … algorithm. Moreover, to preserve desirable population diversity and improve the searching efficiency, we propose different … problem-specific evolutionary strategies. Finally, we test the performance of our proposed memetic algorithm with other state …

Genetic Algorithms (GA) are metaheuristic techniques for combinatorial optimization problems. ABC and PSO are swarm … intelligence based approaches and they are nature-inspired optimization algorithms. In this study ABC and PSO supported GA … Turkey. ABC and PSO-based GA algorithms are applied to solve the travelling salesman problem and results are compared with …

, which tend to be expensive to solve. In this work, we present a new hybrid multi-objective OvS algorithm, which uses Kriging …-type metamodels to estimate the simulations results and a multi-objective evolutionary algorithm to manage the optimization process … obtained. The evolutionary part of the hybrid algorithm is based on the popular NSGA-II. The hybrid method is compared to the …

development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic … Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search … algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated …