Battle royale optimization algorithm

Recently, several metaheuristic optimization approaches have been developed for solving many complex problems in various areas. Most of these optimization algorithms are inspired by nature or the social behavior of some animals. However, there is no optimization algorithm which has been inspired by...

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Bibliographic Details
Published in:Neural computing & applications Vol. 33; no. 4; pp. 1139 - 1157
Main Author: Rahkar Farshi, Taymaz
Format: Journal Article
Language:English
Published: London Springer London 01.02.2021
Springer Nature B.V
Subjects:
Algorithms
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer & video games
Computer Science
Data Mining and Knowledge Discovery
Heuristic methods
Image Processing and Computer Vision
Inverse kinematics
Optimization
Optimization algorithms
Original Article
Probability and Statistics in Computer Science
Robot arms
Metaheuristic
Swarm intelligence
Optimization
Battle royale
ISSN:0941-0643, 1433-3058
Online Access:Get full text
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Summary:Recently, several metaheuristic optimization approaches have been developed for solving many complex problems in various areas. Most of these optimization algorithms are inspired by nature or the social behavior of some animals. However, there is no optimization algorithm which has been inspired by a game. In this paper, a novel metaheuristic optimization algorithm, named BRO (battle royale optimization), is proposed. The proposed method is inspired by a genre of digital games knowns as “battle royale.” BRO is a population-based algorithm in which each individual is represented by a soldier/player that would like to move toward the safest (best) place and ultimately survive. The proposed scheme has been compared with the well-known PSO algorithm and six recent proposed optimization algorithms on nineteen benchmark optimization functions. Moreover, to evaluate the performance of the proposed algorithm on real-world engineering problems, the inverse kinematics problem of the 6-DOF PUMA 560 robot arm is considered. The experimental results show that, according to both convergence and accuracy, the proposed algorithm is an efficient method and provides promising and competitive results.
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ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-020-05004-4