Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/161
Title: | JayaX: Jaya algorithm with xor operator for binary optimization | Authors: | Aslan, Murat Gündüz, Mesut Kıran, Mustafa Servet |
Keywords: | Jaya Binary Optimization Logic Operator Exclusive Or Differential Evolution Algorithm Particle Swarm Optimization Bee Colony Algorithm Artificial Algae Algorithm Global Harmony Search Parameter-Estimation Design Optimization Location-Problems Model |
Publisher: | ELSEVIER | Abstract: | Jaya is a population-based heuristic optimization algorithm proposed for solving constrained and unconstrained optimization problems. The peculiar distinct feature of Jaya from the other population-based algorithms is that it updates the positions of artificial agent in the population by considering the best and worst individuals. This is an important property for the algorithm to balance exploration and exploitation on the solution space. However, the basic Jaya cannot be applied to binary optimization problems because the solution space is discretely structured for this type of optimization problems and the decision variables of the binary optimization problems can be element of set [0,1]. In this study, we first focus on discretization of Jaya by using a logic operator, exclusive or - xor. The proposed idea is simple but effective because the solution update rule of Jaya is replaced with the xor operator, and when the obtained results are compared with the state-of-art algorithms, it is seen that the Jaya-based binary optimization algorithm, JayaX for short, produces better quality results for the binary optimization problems dealt with the study. The benchmark problems in this study are uncapacitated facility location problems and CEC2015 numeric functions, and the performance of the algorithms is compared on these problems. In order to improve the performance of the proposed algorithm, a local search module is also integrated with the JayaX. The obtained results show that the proposed algorithm is better than the compared algorithms in terms of solution quality and robustness. (C) 2019 Elsevier B.V. All rights reserved. | URI: | https://doi.org/10.1016/j.asoc.2019.105576 https://hdl.handle.net/20.500.13091/161 |
ISSN: | 1568-4946 1872-9681 |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
Files in This Item:
File | Size | Format | |
---|---|---|---|
1-s2.0-S1568494619303564-main.pdf Until 2030-01-01 | 3.22 MB | Adobe PDF | View/Open Request a copy |
CORE Recommender
SCOPUSTM
Citations
35
checked on Aug 10, 2024
WEB OF SCIENCETM
Citations
69
checked on Aug 10, 2024
Page view(s)
112
checked on Aug 12, 2024
Download(s)
8
checked on Aug 12, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.