The increase in available data has attracted the interest in clustering approaches as a way
of coherently aggregating them and identify patterns in big data. Hence, Swarm Intelligence …

With Cloud computing becoming mainstream for the execution of various applications, the
multi-objective scheduling algorithms for providing the most suitable services to users have …

Multi-objective optimization is many important since most of the real world problems are in
multi-objective category. Looking at the literature, the algorithms proposed for the solution of …

Fog computing paradigm attempts to provide diverse processing at the edge of IoT networks.
Energy usage being one of the important elements that may have a direct influence on the …

Multi-cloud is the use of multiple cloud computing in a single heterogeneous architecture.
Workflow scheduling in multi-cloud computing is an NP-Hard problem for which many …

This study investigates a multi-objective Vortex Search algorithm (MOVS) by modifying the
single-objective Vortex Search algorithm or VS. The VS is a metaheuristic-based algorithm …

Nature-inspired computing has attracted a lot of research effort especially for addressing
real-world multi-objective optimization problem (MOP). This paper proposes a new nature …

Most of the traditional Recommendation Systems (RSs) focus on recommending only the
popular items as they deal with a single objective precision/popularity. However, focusing on …

Since the industrial robots are incrementally utilized in U-shaped assembly lines to replace
operators, the focus of these lines is not only on productivity improvement, but also more on …

Among the nature inspired heuristic or meta-heuristic optimization algorithms, Bee Colony
Optimization (BCO) algorithms are widely used to solve clustering problem. In this paper, a …