In this paper, a multimodal function optimization problem consisting of multiple maximums and multiple minimums is solved using an improved particle swarm optimization (PSO) …
Metaheuristic approaches with extremely important improvements are very promising in the solution of intractable optimization problems. The objective of the present study is to test the …
D Chen, F Zou, Z Li, J Wang, S Li - Information Sciences, 2015 - Elsevier
Teaching–learning-based optimization (TLBO) is a recently proposed population-based algorithm that simulates the process of teaching and learning. Compared with other …
S Jiang, J Shang, J Guo, Y Zhang - Applied Sciences, 2023 - mdpi.com
To overcome the limitations of the Flamingo Search Algorithm (FSA), such as a tendency to converge on local optima and improve solution accuracy, we present an improved algorithm …
T Ray, KM Liew - Engineering optimization, 2002 - Taylor & Francis
This paper presents a new optimization algorithm to solve multiobjective design optimization problems based on behavioral concepts similar to that of a real swarm. The individuals of a …
Abstract The Salp Swarm Algorithm (SSA) is an effective single-objective optimization algorithm that was inspired by the navigating and foraging behaviors of salps in their natural …
S Kumar, R Kumari, VK Sharma - Procedia Computer Science, 2015 - Elsevier
Abstract Spider Monkey Optimization (SMO) technique is most recent member in the family of swarm optimization algorithms. SMO algorithm fall in class of Nature Inspired Algorithm …
This book is motivated by the fact that meta-heuristic optimization techniques have become very popular among researchers and engineers over the last two decades. The widespread …
Over the past decade, solving complex optimization problems with metaheuristic algorithms has attracted many experts and researchers. There are exact methods and approximate …