The shuffled frog leaping algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …

This paper proposes using the opposition-based learning (OBL) strategy in the shuffled frog
leaping (SFL). The SFL divides a population into several memeplexes and then improves …

Shuffled frog leaping (SFL) is a population based, cooperative search metaphor inspired by
natural memetics. Its ability of adapting to dynamic environment makes SFL become one of …

Currently, the masses are interested in sharing opinions, feedbacks, suggestions on any
discrete topics on websites, e-forums, and blogs. Thus, the consumers tend to rely a lot on …

Abstract Shuffled Frog Leaping Algorithm (SFLA) is one of the most widespread algorithms.
It was developed by Eusuff and Lansey in 2006. SFLA is a population-based metaheuristic …

Seagull optimization algorithm (SOA) is a recent bio-inspired technique utilized to improve
the constrained large-scale problems in low computational cost and quick convergence …

In this paper, a modification of the newly proposed antlion optimization (ALO) is introduced
and applied to feature selection relied on the Lèvy flights. ALO method is one of the …

Several types of evolutionary computing methods are documented in the literature and are
well known for solving unconstrained optimisation problems. This paper proposes a hybrid …

There are various fields are affected by the growth of data dimensionality. The major
problems which are resulted from high dimensionality of data including high memory …

According to the manufacturer's IV data, we need to obtain the best parameters for
assessing the photovoltaic systems. Although much work has been done in this area, it is …