Many real world engineering optimization problems are multi-modal and associated with
constrains. The multi-modal problems involve presence of local optima and thus …

Cloud computing becomes a promising technology to reduce computation cost by providing
users with elastic resources and application-deploying environments as a pay-per-use …

Cloud computing has emerged as a high-performance computing environment with a large
pool of abstracted, virtualized, flexible, and on-demand resources and services. Scheduling …

This book presents a general framework to implement a link between process simulators
and optimization through metaheuristic techniques. The book describes step-by-step the …

This paper presents a comprehensive study on the design optimization of a robotic gripper,
focusing on both the gripper modeling and the optimization of its parallel mechanism …

Symbiotic organisms search (SOS) algorithm is a current popular stochastic optimization
algorithm. It has been widely used to handle all kinds of optimization problems, whereas …

An improved basic artificial bee colony (ABC) algorithm with a self-adaptive technique,
called dynamic ABC, is proposed. The dynamic ABC algorithm first uses a hybrid method …

Weight and bias connection are important features of neural networks, which is still
challenging for researchers. In this work, we focus on initial weights and bias connection of …

Aiming at the problem that the Harris hawk optimization (HHO) algorithm does not have high
optimization accuracy and is prone to fall into local optimum, an improved Harris hawk …

With the rapid development of data collection methods and their practical applications, the
management of uncertain data streams has drawn wide attention in both academia and …