Paper Info
Title
Emperor penguin optimizer: A bio-inspired algorithm for engineering problems.
Abstract
This paper proposes a novel optimization algorithm, called Emperor Penguin Optimizer (EPO), which mimics the huddling behavior of emperor penguins (Aptenodytes forsteri). The main steps of EPO are to generate the huddle boundary, compute temperature around the huddle, calculate the distance, and find the effective mover. These steps are mathematically modeled and implemented on 44 well-known benchmark test functions. It is compared with eight state-of-the-art optimization algorithms. The paper also considers for solving six real-life constrained and one unconstrained engineering design problems. The convergence and computational complexity are also analyzed to ensure the applicability of proposed algorithm. The experimental results show that the proposed algorithm is able to provide better results as compared to the other well-known metaheuristic algorithms.
Year
DOI
Venue
2018
10.1016/j.knosys.2018.06.001
Knowledge-Based Systems
Keywords
Field
DocType
Optimization techniques,Metaheuristics,Constrained optimization,Unconstrained optimization,Benchmark test functions
Aptenodytes,Convergence (routing),Computer science,Algorithm,Emperor,Engineering design process,Optimization algorithm,Computational complexity theory,Metaheuristic
Journal
Volume
ISSN
Citations 
159
0950-7051
28
PageRank 
References 
Authors
0.81
28
2
Name
Order
Citations
PageRank
Gaurav Dhiman163632.82
Vijay Kumar222921.59