Abstract: Constrained multi-objective problems (CMOPs) are tricky, because it is difficult to handle multiple objectives and constraints simultaneously. Most existing algorithms perform well on CMOPs ...

Researchers have developed a novel multi-constraint optimization method that significantly improves the efficiency of reinforcement learning in complex environments. This new algorithm, called ...

UAV swarms have shown immense potential for applications ranging from disaster response to military reconnaissance, but ensuring reliable communication in contested environments has remained a ...

Management of groundwater quality in agricultural areas requires tradeoffs between competing objectives. These objectives include economic benefit, respect for regulatory-imposed water quality ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

This repository contains the MATLAB source code and associated data files to support the findings of the paper: [To be included upon publication]. The code facilitates the simulation, analysis, and ...

This repository contains the code to run the experiments in the paper (Buckingham et al., 2025): Buckingham, J. M., Rojas Gonzalez, S., & Branke, J. (2025). Knowledge Gradient for Multi-Objective ...

Abstract: In this paper, we propose a Multi-objective Particle Swarm Optimization (MOPSO) approach based on a decomposition framework with constraint-handling mechanisms to solve Constrained ...