Recent years have witnessed the use of metaheuristic algorithms to solve the optimization
problems that usually require extensive computations and time. Among others, scatter …

Solving optimization problems is an ever-growing subject with an enormous number of
algorithms. Examples of such algorithms are Scatter Search (SS) and genetic algorithms …

Scatter search (SS) is a population-based metaheuristic algorithm, which has been proved
high efficiency and effective optimizer for complex continuous real value problems. A two …

The area coverage problem solution is one of the vital research areas which can benefit
from swarm robotics. The greatest challenge to the swarm robotics system is to complete the …

This work aims to improve the performance of the Bees Algorithm (BA), particularly in terms
of simplicity, accuracy, and convergence. Three improvements were made in this study as a …

The bee colony optimization (BCO) algorithm with a linear dance function (denoted as the
BCO‐Linear algorithm) is inspired by the bees' foraging behaviors, in which waggle dances …

The Scatter Search (SS) is a deterministic strategy that has been applied successfully to
some combinatorial and continuous optimization problems. Cuckoo Search (CS) is heuristic …

ABSTRACT A modified Scatter Search (SS) algorithm based on Meerkat Clan Algorithm
(MCA) has been presented in this paper. SS is one of the important metaheuristic …

A novel hybrid cooperative scatter search (SS) algorithm with an elite learning mechanism
(HSSA) is proposed for addressing complex continuous global optimization problems. The …

ABSTRACT A simple and effective mechanism is quite required for the industry to optimise
the factors such as depth of cut, feed and cutting speed, since these parameters influence …