1 code implementation • 25 Mar 2024 • Rui Zhong, Yuefeng Xu, Chao Zhang, Jun Yu
In this paper, we borrow the large language model (LLM) ChatGPT-3. 5 to automatically and quickly design a new metaheuristic algorithm (MA) with only a small amount of input.
1 code implementation • 15 Mar 2024 • Rui Zhong, Yuefeng Xu, Chao Zhang, Jun Yu
This paper introduces a novel metaheuristic algorithm, known as the efficient multiplayer battle game optimizer (EMBGO), specifically designed for addressing complex numerical optimization tasks.
no code implementations • 31 Dec 2023 • Yuefeng Xu, Rui Zhong, Chao Zhang, Jun Yu
Various popular multiplayer battle royale games share a lot of common elements.
no code implementations • 13 Oct 2022 • Rui Zhong, Enzhi Zhang, Masaharu Munetomo
Based on this hypothesis, in each generation of optimization, we replace the worst individual in Evolutionary Algorithms (EAs) with the elite individual to participate in the evolution process.
no code implementations • 27 Sep 2022 • 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 participation of a well-performed individual as an elite can accelerate the convergence of optimization.
no code implementations • 2 Sep 2022 • Rui Zhong, Masaharu Munetomo
Simulation experiments and mathematical analysis show that aRG can detect the interactions between variables without the fitness landscape knowledge, and the sub-problems decomposed by aRG have smaller scales, which is easier for EAs to optimize.
no code implementations • 31 Aug 2022 • Rui Zhong, Masaharu Munetomo
In this paper, we propose a simple strategy for estimating the convergence point approximately by averaging the elite sub-population.
no code implementations • 29 Aug 2022 • Rui Zhong, Masaharu Munetomo
In the variable grouping stage, according to our previous research, we treat the variable grouping problem as a combinatorial optimization problem, and the linkage measurement function is designed based on linkage identification by the nonlinearity check on real code (LINC-R).
no code implementations • 25 Apr 2022 • Xiaochen Li, Rui Zhong, Jian Liang, Xialong Liu, Yu Zhang
Rich user behavior information is of great importance for capturing and understanding user interest in click-through rate (CTR) prediction.