Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

Three Opinion writers break down the former vice president’s book of excuses. By Michelle Cottle Carlos Lozada and Lydia Polgreen Produced by Vishakha Darbha Three Opinion writers weigh in on Kamala ...

Abstract: Plenty of decision variable grouping-based algorithms have shown satisfactory performance in solving high-dimensional optimization problems. However, most of them are tailored for ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Abstract: A wide range of real applications can be modelled as the multiobjective traveling salesman problem (MOTSP), one of typical combinatorial optimization problems. Meta-heuristics can be used to ...

1 School of Mathematics and Statistics, Fuzhou University, Fuzhou, China. 2 College of Computer and Data Science, Fuzhou University, Fuzhou, China. In this paper, we use Physics-Informed Neural ...

The paper presents a topology optimization methodology for 2D elastodynamic problems using the boundary element method (BEM). The topological derivative is derived based on the variation method and ...

1 Department of Engineering, University of Ferrara, Ferrara, Italy 2 Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy Integration between constrained optimization ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...