Portfolio optimization has been studied extensively by researchers in computer science and
finance, with new and novel work frequently published. Traditional methods, such as …

In recent years, swarm intelligence optimization algorithms have been proven to have
significant effects in solving combinatorial optimization problems. Introducing the concept of …

In this paper, we present a model-free tracking controller for a cooperative mobile-
manipulators, which are the cornerstone for future smart homes. The mobile-manipulators …

In this paper, we present a fraud detection framework for publicly traded firms using an
optimization approach integrated with a meta-heuristic algorithm known as Beetle Antennae …

In this paper, we propose a control framework for cooperative robotic agents, which
constitutes an essential component in the construction of futuristic smart-homes. Such …

With the advances in time-series prediction, several recent developments in machine
learning have shown that integrating prediction methods into portfolio selection is a great …

This paper proposes a continuous-time enhanced variant of Beetle Antennae Search (BAS),
a metaheuristic algorithm that mimics the food searching nature of beetles. Beetles register …

In this brief, we presented a framework for the trajectory optimization of the 5-link Biped
Robot using the Beetle Antennae Search (BAS) algorithm. The biped robot is highly non …

Portfolio analysis is a crucial subject within modern finance. However, the classical
Markowitz model, which was awarded the Nobel Prize in Economics in 1991, faces new …

Abstract A 1–0 Bg-RRT algorithm is proposed to reduce computational time and complexity,
even in complex environments. Different from Rapidly-exploring Random Tree (RRT) and …