Scalability of optimization algorithms is a major challenge in coping with the ever-growing
size of optimization problems in a wide range of application areas from high-dimensional …

This article is the second part of a two-part survey series on large-scale global optimization.
The first part covered two major algorithmic approaches to large-scale optimization, namely …

Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …

People can use credit cards for online transactions as it provides an efficient and easy-to-
use facility. With the increase in usage of credit cards, the capacity of credit card misuse has …

Computationally efficient algorithms for large-scale black-box optimization have become
increasingly important in recent years due to the growing complexity of engineering and …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a
growing research topic with many competitive bio-inspired algorithms being proposed every …

Evolutionary algorithms (EAs) have become one of the most effective techniques for multi-
objective optimization, where a number of variation operators have been developed to …

Large-scale optimization problems (LSOPs) are challenging because the algorithm is
difficult in balancing too many dimensions and in escaping from trapped bottleneck …

As a form of evolutionary computation, particle swarm optimization is less effective in large
scale optimization since it is unable to effectively balance exploration and exploitation. To …