Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …

Multimodal optimization (MMO) aiming to locate multiple optimal (or near-optimal) solutions
in a single simulation run has practical relevance to problem solving across many fields …

In this paper, a novel swarm-based metaheuristic algorithm inspired from the behaviors of
beluga whales, called beluga whale optimization (BWO), is presented to solve optimization …

Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

Locating multiple roots of nonlinear equation systems (NESs) remains a challenging and
meaningful task in the numerical optimization community. Although a large number of NES …

Imbalanced data with a skewed class distribution are common in many real-world
applications. Deep Belief Network (DBN) is a machine learning technique that is effective in …

Optimization is a branch of applied mathematics and numerical analysis. Almost every
problem in engineering, science, economics, and life can be formulated as an optimization …

Batch-processing machines (BPMs) can process a number of jobs at a time, which can be
found in many industrial systems. This article considers a single BPM scheduling problem …

In population-based optimization algorithms (POAs), given an optimization problem, the
quality of the solutions depends heavily on the selection of algorithms, strategies and …