14 citations · 18 across the 9 of their papers we have counts for
5 papers · 1 filter
Accelerating the Evolutionary Algorithms by Gaussian Process Regression with -greedy acquisition function
Rui Zhong, Enzhi Zhang, Masaharu Munetomo
In this paper, we propose a novel method to estimate the elite individual to accelerate the convergence of optimization. Inspired by the Bayesian Optimization Algorithm (BOA), the…
Accelerating the Genetic Algorithm for Large-scale Traveling Salesman Problems by Cooperative Coevolutionary Pointer Network with Reinforcement Learning
Rui Zhong, Enzhi Zhang, Masaharu Munetomo
In this paper, we propose a two-stage optimization strategy for solving the Large-scale Traveling Salesman Problems (LSTSPs) named CCPNRL-GA. First, we hypothesize that the partici…
Cooperative coevolutionary Modified Differential Evolution with Distance-based Selection for Large-Scale Optimization Problems in noisy environments through an automatic Random Grouping
Rui Zhong, Masaharu Munetomo
Many optimization problems suffer from noise, and nonlinearity check-based decomposition methods (e.g. Differential Grouping) will completely fail to detect the interactions betwee…
Accelerating differential evolution algorithm with Gaussian sampling based on estimating the convergence points
Rui Zhong, Masaharu Munetomo
In this paper, we propose a simple strategy for estimating the convergence point approximately by averaging the elite sub-population. Based on this idea, we derive two methods, whi…
Cooperative coevolutionary hybrid NSGA-II with Linkage Measurement Minimization for Large-scale Multi-objective optimization
Rui Zhong, Masaharu Munetomo
In this paper, we propose a variable grouping method based on cooperative coevolution for large-scale multi-objective problems (LSMOPs), named Linkage Measurement Minimization (LMM…