Abstract: With the development of deep learning, the traditional approach of manually designing network archi-tectures and determining parameters inevitably loses its reliance on expert systems, which ...

A multi-algorithm optimization framework for cooperative electric vehicle fleet routing and charging on realistic road networks. Compares five approaches — Simulated Annealing (SA), Genetic Algorithm ...

In a disaster, every second is critical. Large-scale disasters, such as earthquakes, hurricanes, and landslides, often involve trapped or stranded survivors in need of rescue, and locating them as ...

ABSTRACT: This study focused on optimizing distribution networks through the strategic integration of photovoltaic (PV) systems and D-STATCOM compensators. Using the particle swarm optimization (PSO) ...

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 ...

In this tutorial, we implement an advanced Optuna workflow that systematically explores pruning, multi-objective optimization, custom callbacks, and rich visualization. Through each snippet, we see ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Abstract: Path planning is a key challenge in the field of mobile robotics. However, the standard particle swarm optimization (PSO) has some significant limitations when dealing with path planning ...

The development of large language models has given rise to emerging markets where companies offer models as a service and compete for user usage. A concern is that the accumulation of data and compute ...