During the past few years, research in applying machine learning (ML) to design efficient,
effective, and robust metaheuristics has become increasingly popular. Many of those …

Bayesian optimization (BO) is a powerful approach for seeking the global optimum of
expensive black-box functions and has proven successful for fine tuning hyper-parameters …

This study aims to develop a time-efficient yet high-performance solution algorithm to
address a facility location problem with uniformly distributed demand along the network …

Advancements in computing and storage technologies have significantly contributed to the
adoption of deep learning (DL)-based models among machine learning experts. Although a …

Bayesian inference is used to extract unknown parameters from gravitational-wave signals.
Detector noise is typically modeled as stationary, although data from the LIGO and Virgo …