Mar 16, 2020 · The main focus of this paper is on the family of evolutionary algorithms and their real-life applications. We present the following algorithms: genetic algorithms, genetic programming, …

3 days ago · Addressing a Key Research Gap Most prior work: single-mode or single-objective networks. Evolutionary algorithms for routing limited to small networks. Paper fills gap: multi-mode + …

Nov 1, 2024 · To address these problems, this paper proposes an efficient optimization algorithm called alpha evolution (AE). A distinctive operator was designed in AE to drive optimization by incorporating …

Jan 1, 2008 · This paper proposes a multiobjective evolutionary algorithm based on decomposition (MOEA/D). It decomposes a multiobjective optimization problem into a number of scalar optimization …

This paper proposes a multiobjective evolutionary algorithm based on decomposition (MOEA/D). It decomposes a multiobjective optimization problem into a number of scalar optimization subproblems …

Sep 14, 2015 · This paper proposes a method for energy efficiency optimization in simple humanoid robot locomotion using a single-objective genetic algorithm.

Dec 14, 2023 · FunSearch makes discoveries in established open problems using large language models by searching for programs describing how to solve a problem, rather than what the solution is.

Apr 1, 2024 · This paper presents a comprehensive survey on integrating reinforcement learning into the evolutionary algorithm, referred to as reinforcement learning-assisted evolutionary algorithm (RL …

Mar 2, 2025 · In response to the limitations of reinforcement learning and Evolutionary Algorithms (EAs) in complex problem-solving, Evolutionary Reinforcement Learning (EvoRL) has emerged as a …

May 17, 2023 · We propose an efficient evolutionary algorithm based on deep reinforcement learning to solve large-scale SMOPs. Deep reinforcement learning networks are used for mining sparse …