Abstract: Bayesian Optimization (BO) has shown promise in tuning processor design parameters. However, standard BO does not support constraints involving categorical parameters such as types of branch ...

Develop optimal solutions to a scheduling problem by modelling it as a Constraint Satisfaction Problem (CSP), a method used widely in the field of Artificial Intelligence. I've open-sourced Delegator ...

Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...

SLSQP stands for Sequential Least Squares Programming. It is a numerical optimization algorithm used to solve constrained nonlinear optimization problems. In this project, we aim to optimize objective ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, performance, and real-world applicability by introducing FlexQAOA, a hybrid ...

Artificial intelligence (AI) is playing a huge role in heat rate optimization. In some cases, AI-driven models have analyzed operational data to recommend control settings that reduce heat rates by ...