Abstract: Surrogate-based-constrained optimization for some optimization problems involving computationally expensive objective functions and constraints is still a great challenge in the optimization ...

Globally, subtle hydrocarbon reservoirs in petroliferous basins have always been challenging targets for exploration research, with thin sand body reservoir prediction being a key focus in this field.

For more than 30 years, the solar industry has been built around rectangular panels. Everything, from cutting the silicon cells to framing, shipping, mounting, and connecting them to inverters, has ...

Abstract: Expensive constrained optimization problems are prevalent in many engineering domains, where evaluating objective and constraints requires costly simulations or physical experiments. As ...

Factor graph optimization serves as a fundamental framework for robotic perception, enabling applications such as pose estimation, simultaneous localization and mapping (SLAM), structure-from-motion ...

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 ...

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 ...

Traditional approaches to analytical method optimization (e.g., univariate and “guess-and-check”) can be time-consuming, costly, and often fail to identify true optima within the parameter space.

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