This review aims to exploit a study on different benchmark test functions used to evaluate the
performance of Meta-Heuristic (MH) optimization techniques. The performance of the MH …

Imitation learning techniques aim to mimic human behavior in a given task. An agent (a
learning machine) is trained to perform a task from demonstrations by learning a map** …

This paper proposes a new metaheuristic optimization algorithm based on ancient war
strategy. The proposed War Strategy Optimization (WSO) is based on the strategic …

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

Practical optimization problems often involve a large number of variables, and solving them
in a reasonable amount of time becomes a challenge. Competitive swarm optimizer (CSO) is …

Large-scale optimization problems (LSOPs) have drawn researchers' increasing attention
since their resemblance to real-world problems. However, due to the complex search space …

A large number of intelligent algorithms based on social intelligent behavior have been
extensively researched in the past few decades, through the study of natural creatures, and …

High-dimensional and sparse (HiDS) matrices are frequently found in various industrial
applications. A latent factor analysis (LFA) model is commonly adopted to extract useful …

Many optimization problems in reality involve both continuous and discrete decision
variables, and these problems are called mixed-variable optimization problems (MVOPs) …

Cyber-security garnered significant attention due to the increased dependency of individuals
and organizations on the Internet and their concern about the security and privacy of their …