Optimal reactive power dispatch using an adaptive genetic algorithm

Space Exploration of Multi-agent Robotics via Genetic Algorithm

“…1. As suggested by most GA researchers [7,8,9,10], the probabilities of crossover which are used in this experiment range from 0.5 to 0.9. The other simulation parameters are given in Table 1.…”

Two Population-Based Heuristic Search Algorithms and Their Applications

“…For the afore-mentioned DEs, since the local search schedule used in [43] can clearly improve their performances, the improved versions of the three DEs with local search, instead of their corresponding original versions, are used in this study and denoted as L-DE, L-SACP-DE and L-SaDE, respectively. Moreover, a canonical genetic algorithm (CGA) and an adaptive genetic algorithm (AGA) introduced in [55] are implemented for comparison with SOA. The fmincon-based nonlinear programming method (NLP) [45,56] is also considered.…”

“…The realvalue position of the seeker consists of three parts: generator voltages, transformer taps and shunt capacitors/inductors. According to the section 3.4 of this paper, after the update of the position, the main program is turned to the sub-program for evaluating the objective function where the latter two parts of the position are truncated into the corresponding integers as [44,55]. Then, the real-value position is changed into a mixed-variable vector which is used to calculate the objective function value by equation (23) based on NewtonRaphson power flow analysis [45].…”

A review on applications of heuristic optimization algorithms for optimal power flow in modern power systems

“…The proposed multi-objective evolutionary algorithm demonstrates superiority in comparisons to PSO-Fuzzy approach. An adaptive genetic algorithm (AGA) was developed to solve OPF problems and voltage control [27], where the probabilities of crossover and mutation were adjusted in terms of the fitness values of the solutions and the normalized fitness distances between the solutions in the evolution process. In [28], a refined genetic algorithm (RGA) was developed for solving OPF problem.…”