We walk through an optimization problem step by step, clearly explaining how to identify variables, set up the correct function, apply derivatives, and find maximum or minimum values. Each step is ...

Implementation of numerical optimization algorithms in MATLAB, including derivative-free and gradient-based methods for unconstrained problems, and projection techniques for constrained optimization.

Python and MATLAB are valuable for an electrical engineer's career, but the better choice depends on your field, industry, and career goals. Electrical engineers face many challenges: dealing with ...

Heidi S. Enger ’27, an Associate Editorial Editor, is a Social Studies Concentrator in Eliot House. She’s enrolled in Ec10b this semester (don’t ask). Harvard students have to stop treating life like ...

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 ...

Abstract: The field of power systems often requires optimization techniques to solve complex problems. One such problem is the unit commitment problem (UCP), which involves finding the optimal ...

LETO is a new hybrid Lagrangian-Eulerian method for topology optimization. It transfers density information from movable Lagrangian carriers to a fixed set of Eulerian quadratures and solves force ...

Abstract: The MATLAB toolbox YALMIP is introduced. It is described how YALMIP can be used to model and solve optimization problems typically occurring in systems and control theory. In this paper, ...