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Solving Multi-Objective Resource Allocation Problem Using Multi-Objective Binary Artificial Bee Colony Algorithm

Arabian Journal for Science and Engineering · Eylül 2021

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YÖKSİS Kayıtları
Solving Multi‑Objective Resource Allocation Problem Using Multi‑Objective Binary Artificial Bee Colony Algorithm
Arabian Journal for Science and Engineering · 2021 SCI-Expanded
Dr. Öğr. Üyesi ZÜLEYHA YILMAZ ACAR →
Solving Multi‑Objective Resource Allocation Problem Using Multi‑Objective Binary Artificial Bee Colony Algorithm
Arabian Journal for Science and Engineering · 2021 SCI-Expanded
Prof. Dr. FATİH BAŞÇİFTÇİ →
YÖKSİS ISSN Eşleşmesi

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Solving Multi‑Objective Resource Allocation Problem Using Multi‑Objective Binary Artificial Bee Colony Algorithm
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Determination of Temperature Effects on Cortical Bone Milling Using Taguchi Method
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Makale Bilgileri

Dergi Arabian Journal for Science and Engineering
ISSN2193567X
Yayın TarihiEylül 2021
Cilt / Sayfa46 · 8535-8547
DOI10.1007/s13369-021-05521-x
Scopus ID2-s2.0-85103615369
Özet Resource allocation is the optimal distribution in a limited number of resources available for certain activities. The allocation of the resources for a large number of activities requires exponentially multiplying a computation cost. Therefore, the resource allocation problem is known as NP-Hard problem in the literature. In this study, a multi-objective binary artificial bee colony algorithm has been proposed for solving the multi-objective resource allocation problems. The proposed algorithm has benefited from the robust structure and easy implementation properties of the artificial bee colony algorithm. The contribution is to introduce the multi-objective version of the artificial bee colony algorithm with advanced local search and binary format using transfer functions. The multi-objective binary artificial bee colony algorithm has been improved as two versions using sigmoid and hyperbolic tangent transfer functions to be able to search in the binary search space. With the proposed algorithms, the multi-objective resource allocation problems in the literature are solved, and the algorithms are compared with other algorithms that develop for the same problems. The results obtained show that the proposed algorithms give effective results on the problem. Especially, in large-scale problems, higher accuracy values are reached with a smaller number of evaluations.

Yazarlar (2)

1
Züleyha Yılmaz Acar
2
Fatih Başçiftçi

Anahtar Kelimeler

Artificial Bee Colony Algorithm Binary Optimization Multi-objective Optimization Multi-objective Resource Allocation Problem Transfer Functions

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Arabian Journal for Science and Engineering
Q1
SJR Skoru0,545
H-Index89
ÜlkeGermany
Multidisciplinary (Q1)
Dergi sayfasına git

Metrikler

14
Atıf
2
Yazar
5
Anahtar Kelime

Sistemimizdeki Yazarlar

ZY
ZÜLEYHA YILMAZ ACAR
Dr. Öğr. Üyesi

Hızlı Erişim

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