Multi-objective optimization for stochastic computer networks using NSGA-II and TOPSIS

GIS-modelling based coal-fired power plant site identification and selection

“…NSGA-II has a fast non-dominated sorting approach, a fast crowded distance estimation procedure and a simple crowded comparison operator [32]. It is popular and reliable in various fields, such as in stochastic computer network optimization [34], and reactive power planning [33,35]. Algorithm 1 shows the operation framework of NSGA-II in the methodology.…”

“…Here, the NSGA-II is applied because of its superior computational capacity. The NSGA-II was initially proposed by Deb et al [32] and has been widely applied to various problems [33][34][35].…”

A multi objective optimization approach for flexible job shop scheduling problem under random machine breakdown by evolutionary algorithms

“…These features have made the NSGA-II very effective in solving the FJSP. In this paper, NSGA-II is used for solving this problem, as it has recently been applied to solve several different problems [10,19,27]. Another well-known MOEA, a modified version of the NSGA-II, is called non-dominated ranking genetic algorithm (NRGA) proposed by Al Jadaan et al [3].…”

Developing and Multi-Objective Optimization of a Combined Energy Absorber Structure Using Polynomial Neural Networks and Evolutionary Algorithms

“…It is now desired to find a trade-off optimum design point from all non-dominated threeobjective optimization processes with the compromising of all objective functions. This can be achieved by the nearest-to-ideal-point method and TOPSIS method (Atashkari et al, 2007) and (Lin and Yeh, 2012).…”