Particle swarm optimization (termed as PSO) is a metaheuristic algorithm inspired by the
swarm intelligence. Since its advent, PSO has been successfully applied to tackle various …

Abstract Network-on-chips (NoCs) have been widely employed in the design of
multiprocessor system-on-chips (MPSoCs) as a scalable communication solution. NoCs …

We describe algorithmic enhancements to a decision-support tool that residential
consumers can utilize to optimize their acquisition of electrical energy services. The decision …

This paper introduces the Botox Optimization Algorithm (BOA), a novel metaheuristic
inspired by the Botox operation mechanism. The algorithm is designed to address …

Particle Swarm Optimization (PSO) has shown an effective performance for solving variant
benchmark and real-world optimization problems. However, it suffers from premature …

Much environmental and socioeconomic time-series data can be adequately modeled using
autoregressive integrated moving average (ARIMA) models. We call such time series" …

Particle swarm optimization algorithms are often applied to solve optimization problems.
However, the traditional particle swarm optimization algorithm has a single search method …

In this study, a novel meta-heuristic search (MHS) algorithm for constrained global
optimization problems is proposed. Since many algorithms aim to achieve well-balanced …

Abstract Industrial Internet of Things (IIoTs) is the fast growing network of interconnected
things that collect and exchange data using embedded sensors planted everywhere. It is an …

A flexible job shop scheduling problem (FJSP) is an extension of the classical job shop
problem (JSP) where operations are allowed to be processed on any among a set of …