Understanding quantum computing, from qubits science and tech breakthroughs to future quantum applications, and discovering how close we are to real-world use cases ...

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 ...

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 ...

You probably don’t need more time. By Jancee Dunn When I look back on all the major decisions I’ve dithered over, I could scream. It took me a decade to commit to becoming a parent. I wavered for a ...

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 recent years, many multimodal multi-objective evolutionary algorithms (MMOEAs) have been proposed for the widely existing multimodal multi-objective optimization problems (MMOPs) in ...

1 Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia 2 Department of Civil, Materials, and Environmental Engineering, The University of Illinois Chicago, Chicago, IL, United ...

Abstract: The main feature of the Dynamic Multi-objective Optimization Problems (DMOPs) is that optimization objective functions will change with times or environments. One of the promising approaches ...