Metaheuristic algorithms are computational intelligence paradigms especially used for
sophisticated solving optimization problems. This chapter aims to review of all …

Cluster analysis is an essential tool in data mining. Several clustering algorithms have been
proposed and implemented, most of which are able to find good quality clustering results …

An original swarm-based, bio-inspired metaheuristic algorithm, named electric eel foraging
optimization (EEFO) is developed and tested in this work. EEFO draws inspiration from the …

In this paper, a novel and powerful metaheuristic optimizer, named the growth optimizer
(GO), is proposed. Its main design inspiration originates from the learning and reflection …

Several metaheuristic optimization algorithms have been developed to solve the real-world
problems recently. This paper proposes a novel metaheuristic algorithm named Henry gas …

The use of metaheuristics is one of the most encouraging methodologies for taking care of
real-life problems. Bald eagle search (BES) algorithm is the latest swarm-intelligence …

Feature selection is an NP-hard problem to remove irrelevant and redundant features with
no predictive information to increase the performance of machine learning algorithms. Many …

Stochastic-based optimization algorithms are effective approaches to addressing
optimization challenges. In this article, a new optimization algorithm called the Election …

In this research article, we uphold the principles of the No Free Lunch theorem and employ it
as a driving force to introduce an innovative game-based metaheuristic technique named …

There are many pressures on the global food system such as urbanization, climate change,
and environmental degradation. Urban agriculture is an approach to producing food inside …