Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/4954
Title: A new binary arithmetic optimization algorithm for uncapacitated facility location problem
Authors: Bas, E.
Yildizdan, G.
Keywords: Arithmetic optimization algorithm
Binary optimization
Logic gate
Uncapacitated facility location problem
Benchmarking
Binary trees
Computer circuits
Location
Logic gates
Optimization
Trees (mathematics)
Arithmetic optimization algorithm
Binary arithmetic
Binary optimization
Continuous optimization problems
Facility location problem
Optimization algorithms
Optimization problems
Seed-algorithm
Uncapacitated facility location problem
Uncapacitated facility locations
Heuristic methods
Issue Date: 2023
Publisher: Springer Science and Business Media Deutschland GmbH
Abstract: Arithmetic Optimization Algorithm (AOA) is a heuristic method developed in recent years. The original version was developed for continuous optimization problems. Its success in binary optimization problems has not yet been sufficiently tested. In this paper, the binary form of AOA (BinAOA) has been proposed. In addition, the candidate solution production scene of BinAOA is developed with the xor logic gate and the BinAOAX method was proposed. Both methods have been tested for success on well-known uncapacitated facility location problems (UFLPs) in the literature. The UFL problem is a binary optimization problem whose optimum results are known. In this study, the success of BinAOA and BinAOAX on UFLP was demonstrated for the first time. The results of BinAOA and BinAOAX methods were compared and discussed according to best, worst, mean, standard deviation, and gap values. The results of BinAOA and BinAOAX on UFLP are compared with binary heuristic methods used in the literature (TSA, JayaX, ISS, BinSSA, etc.). As a second application, the performances of BinAOA and BinAOAX algorithms are also tested on classical benchmark functions. The binary forms of AOA, AOAX, Jaya, Tree Seed Algorithm (TSA), and Gray Wolf Optimization (GWO) algorithms were compared in different candidate generation scenarios. The results showed that the binary form of AOA is successful and can be preferred as an alternative binary heuristic method. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
URI: https://doi.org/10.1007/s00521-023-09261-x
https://hdl.handle.net/20.500.13091/4954
ISSN: 0941-0643
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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