… The algorithm of NSGA-II[5] is a representative example. Since mid-1980s, researchers …
to improve the convergence of NSGA-II using local perturbation. Local perturbation is able to …

… However, the classical NSGA-II suffers from uneven distribution of convergence… NSGA-II
(INSGA-II) by employing two strategies: a crossover operation based on dimension perturbation …

… , mutation with Pmutation and perturbation with Perturbation Ratio otherwise Apply 100 %
… part shows the difference with NSGA-II and the red part shows the difference with NSGA-III. …

… In such a situation, our procedure selects a perturbation of the best solution as new
current solution. The best solution is selected with respect to the criterion expressed by (3). 3) …

… where formula (12) represents the tent map perturbed by the logistic map. When both the …
make the algorithm escaping the local optimum. During replacement, the higher Pareto rank in …

… (NSGA-II) where a polynomial time algorithm is designed to obtain the optimal CVaR for a
given (r, Q). Moreover, a local search method is tailored for the NSGA-II … the perturbed variables…

… local search methods to NSGA-II to solve the mc-MST, we incorporate three well-known local
search algorithms into the NSGA-II … 1) Pareto Local Search (PLS): Pareto Local Search (PLS…

… Furthermore, Non-dominated Sorting Genetic Algorithms-II (NSGA-II) which is a common
and prominent nondomination based genetic algorithm to unravel the multi objective …

… Considering the importance and wide applications of NSGA-II … explore the literature on
NSGA-II and another version called … As a special case of hybrid MOEAs, NSGA-II combining local …

… We will run these algorithms together with NSGA-II in the next … perturbation) rather than
a stable function in rapid decreasing. Stochastic perturbation is better than stable perturbation …