This paper presents the Secant Optimization Algorithm (SOA), a novel mathematics-inspired metaheuristic derived from the Secant Method. SOA enhances search efficiency by repeating vector updates using ...

Enterprise Development Optimizer (EDO) is a meta-heuristic algorithm inspired by the enterprise development process. Although EDO is effective in the optimization field, it suffers from issues such as ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

The goal of a numerical optimization problem is to find a vector of values that minimizes some cost function. The most fundamental example is minimizing the Sphere Function f(x0, x1, .. xn) = x0^2 + ...

Particle swarm optimization isn't usually seen as the first-choice technique for training a neural network but, as James McCaffrey demonstrates, it's a useful alternative. Particle swarm optimization ...

The course is designed to provide engineering students a view of optimization as a tool for engineering decision making. Students will be given a fundamental introduction to the optimization ...