Abstract: This study proposes a multi-objective scheduling optimization algorithm based on reinforcement learning. This method constructs a deep reinforcement learning framework with Actor-Critic as ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Abstract: Surrogate-assisted evolutionary algorithms have demonstrated remarkable success in tackling expensive multi-objective optimization problems. However, their effectiveness diminishes in ...

1 Department of Quantitative Methods, University of Sousse, Sousse, Tunisia 2 Department of Quantitative Methods, College of Business, King Faisal University, Al-Ahsa, Saudi Arabia Introduction: ...

This repository contains the code for the design and optimization of trajectories specifically for Mars Ascent Vehicles (MAVs), using a Multi-Objective Trajectory Optimization (MOTO) framework, with ...

Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...

School of Information Engineering, Qujing Normal University, Qujing, China. Tourism development in emerging destinations requires balancing economic benefits with ecological sustainability. In this ...