Many swarm optimization algorithms have been introduced since the early 60's,
Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms …

In this article, we encompass an analysis of the recent advances in parallel genetic
algorithms (PGAs). We have selected these algorithms because of the deep interest in many …

A swarm of robots is the coordination of multiple robots that can perform a collective task and
solve a problem more efficiently than a single robot. Over the last decade, this area of …

Abstract Teaching–Learning-Based Optimization (TLBO) is a novel swarm intelligence
metaheuristic that is reported as an efficient solution method for many optimization …

Reconfigurable systems have been widely used in practical engineering, especially for the
reconfigurable computing systems and reconfigurable manufacturing systems. The reliability …

Solving optimization problems with parallel algorithms has a long tradition in OR. Its future
relevance for solving hard optimization problems in many fields, including finance, logistics …

Evolutionary algorithms have been reported to be efficient metaheuristics for the
optimization of several NP-Hard combinatorial optimization problems. In addition to their …

Contactless fingerprint recognition is highly promising and an essential component in the
automatic fingerprint identification system. However, due to the inherent characteristic of …

The quadratic assignment problem (QAP) is an NP‐hard combinatorial optimization problem
with a wide variety of applications. Biogeography‐based optimization (BBO), a relatively …

This study is activated by a real-world case of cold chain distribution in the Yangtze River
Delta of China. Due to the uneven spatial distribution of customers, the customers close to …