This paper reviews the application of metaheuristics for optimized sustainable supply chain
management (SSCM). This paper explores the potential of metaheuristics to improve the …

Meta heuristics is an optimization approach that works as an intelligent technique to solve
optimization problems. Evolutionary algorithms, human-based algorithms, physics-based …

Recently, many metaheuristic optimization algorithms have been developed to address real-
world issues. In this study, a new physics-based metaheuristic called Fick's law optimization …

The purpose of community detection in complex networks is to identify the structural location
of nodes. Complex network methods are usually graphical, with graph nodes representing …

Abstract Feature Subset Selection (FSS) is an NP-hard problem to remove redundant and
irrelevant features particularly from medical data, and it can be effectively addressed by …

The optimal power flow (OPF) is a vital tool for optimizing the control parameters of a power
system by considering the desired objective functions subject to system constraints …

Abstract Coronavirus Disease 2019 (COVID-19) is the most severe epidemic that is
prevalent all over the world. How quickly and accurately identifying COVID-19 is of great …

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile
Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray …

Medical technological advancements have led to the creation of various large datasets with
numerous attributes. The presence of redundant and irrelevant features in datasets …

Monkey king evolution (MKE) is a population-based differential evolutionary algorithm in
which the single evolution strategy and the control parameter affect the convergence and the …