Data clustering is an important data mining technique being widely used in numerous
applications. It is a method of creating groups (clusters) of objects, in such a way that objects …

In this paper, a new kind of swarm-based metaheuristic search method, called Elephant
Herding Optimization (EHO), is proposed for solving optimization tasks. The EHO method is …

In nature, the eastern North American monarch population is known for its southward
migration during the late summer/autumn from the northern USA and southern Canada to …

Earthworms can aerate the soil with their burrowing action and enrich the soil with their
waste nutrients. Inspired by the earthworm contribution in nature, a new kind of bio-inspired …

Intelligent optimization algorithms based on evolutionary and swarm principles have been
widely researched in recent years. The artificial bee colony (ABC) algorithm is an intelligent …

In this paper, a new swarm-based metaheuristic algorithm, called elephant herding
optimisation (EHO), is proposed for solving global optimisation tasks, which is inspired by …

For the purpose of enhancing the search ability of the cuckoo search (CS) algorithm, an
improved robust approach, called HS/CS, is put forward to address the optimization …

When solving constrained optimization problems by evolutionary algorithms, an important
issue is how to balance constraints and objective function. This paper presents a new …

Krill herd (KH) has been proven to be an efficient algorithm for function optimization. For
some complex functions, this algorithm may have problems with convergence or being …

A novel hybrid Krill herd (KH) and quantum-behaved particle swarm optimization (QPSO),
called KH–QPSO, is presented for benchmark and engineering optimization. QPSO is …