Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most
frequently used algorithms for solving complex optimization problems. Its flexibility and …

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 …

Recently, the numerical optimization field has attracted the research community to propose
and develop various metaheuristic optimization algorithms. This paper presents a new …

The job-shop scheduling problem (JSP) is NP hard, which has very important practical
significance. Because of many uncontrollable factors, such as machine delay or human …

The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers.
Most of these cliché methods mimic animals' searching trends and possess a small …

A recent set of overused population-based methods have been published in recent years.
Despite their popularity, most of them have uncertain, immature performance, partially done …

Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …

Meta-heuristic algorithms are becoming more prevalent and have been widely applied in
various fields. There are numerous reasons for the success of such techniques in both …

Computationally efficient algorithms for large-scale black-box optimization have become
increasingly important in recent years due to the growing complexity of engineering and …

Numerous optimization problems can be addressed using metaheuristics instead of
deterministic and heuristic approaches. This study proposes a novel population-based …