Scopus
YÖKSİS DOI Eşleşti
SJR Q1
New WOA Variants for Superior Meta-heuristic Optimization with Multiple Hunter Whale Leading
Arabian Journal for Science and Engineering · Aralık 2025
YÖKSİS Kayıtları
New WOA Variants for Superior Meta-heuristic Optimization with Multiple Hunter Whale Leading
Arabian Journal for Science and Engineering · 2025 SCI-Expanded
Dr. Öğr. Üyesi SEMA SERVİ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
New WOA Variants for Superior Meta-heuristic Optimization with Multiple Hunter Whale Leading
2025 ISSN: 2193-567X SCI-Expanded Q2
Dr. Öğr. Üyesi SEMA SERVİ →
A New Lifetime Model: Properties, Estimation, and Applications in Quality Control
2025 ISSN: 2193-567X SCI-Expanded Q2
Arş. Gör. ERDEM CANKUT →
Brain Tumor Detection with Transfer Learning Models Based on Attention Modules
2026 ISSN: 2193-567X SCI-Expanded Q2
Dr. Öğr. Üyesi ZÜLEYHA YILMAZ ACAR →
Effect of Silica/Graphene Nanohybrid Particles on the Mechanical Properties of Epoxy Coatings
2019 ISSN: 2193-567X SCI-Expanded Q3
Doç. Dr. ŞAKİR YAZMAN →
Heuristic Optimization Based on Penalty Approach for Surface Permanent Magnet Synchronous Machines
2020 ISSN: 2193-567X SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
A Method of Classification Performance Improvement Via a Strategy of Clustering-Based Data Elimination Integrated with k-Fold Cross-Validation
2021 ISSN: 2193-567X SCI-Expanded Q2
Dr. Öğr. Üyesi ONUR İNAN →
Training Feed-Forward Multi-Layer Perceptron Artificial Neural Networks with a Tree-Seed Algorithm
2020 ISSN: 2193-567X SCI-Expanded Q3
Doç. Dr. AHMET CEVAHİR ÇINAR →
Solving Multi‑Objective Resource Allocation Problem Using Multi‑Objective Binary Artificial Bee Colony Algorithm
2021 ISSN: 2193-567X SCI-Expanded Q3
Prof. Dr. FATİH BAŞÇİFTÇİ →
Theoretical and Experimental Investigation of the Performance of an Atkinson Cycle Engine
2021 ISSN: 2193-567X SCI-Expanded Q3
Dr. Öğr. Üyesi HALİL ERDİ GÜLCAN →
Optimization of Electricity Generation Parameters with Microbial Fuel Cell Using the Response Surface Method
2022 ISSN: 2193-567X SCI-Expanded Q2
Prof. Dr. ŞAKİR TAŞDEMİR →
The Innovative Approach to Real-Time Detection of Fuel Types Based on Ultrasonic Sensor and Machine Learning
2024 ISSN: 2193-567X SCI-Expanded Q2
Prof. Dr. MEHMET ÇUNKAŞ →
Enhanced Gain Dual-Port Compact Printed Meandered Log-Periodic Monopole Array Antenna Design with Octagonal-Ring Shaped FSS for Broadband 28 GHz Applications
2024 ISSN: 2193-567X SCI-Expanded Q2
Dr. Öğr. Üyesi MEHMET YERLİKAYA →
The Innovative Approach to Real-Time Detection of Fuel Types Based on Ultrasonic Sensor and Machine Learning
2024 ISSN: 2193-567X SCI-Expanded Q2
Dr. Öğr. Üyesi UĞUR TAŞKIRAN →
Determination of Temperature Effects on Cortical Bone Milling Using Taguchi Method
2025 ISSN: 2193-567X SCI-Expanded Q2
Prof. Dr. SÜLEYMAN NEŞELİ →
Characterizing Machining Indicators with Machine Learning Models Under Cellulose Nanocrystal and Graphene-Based Nanofluid Conditions
2025 ISSN: 2193-567X SCI-Expanded Q2
Doç. Dr. MUSTAFA KUNTOĞLU →
Makale Bilgileri
ISSN2193567X
Yayın TarihiAralık 2025
Cilt / Sayfa50 · 20317-20342
Scopus ID2-s2.0-105018491676
Özet
This study introduces three new algorithms, MPW-WOA, MP-WOA, and MPL-WOA, designed to enhance the exploration capability of the well-regarded whale optimization algorithm (WOA), a meta-heuristic optimization technique. These improvements aim to strengthen the exploration capabilities of the algorithm and converge toward the global optimum solution. The focus of WOA on the leader individual may cause the positions of new individuals to get stuck in sub-solutions. To solve this problem, the proposed algorithms aim to obtain stronger and more consistent results by the effect of the best three whales in various ratios instead of a single leader. After the proposed methods are applied 30 times on 23 benchmark test functions, the mean and standard deviation data are examined. This evaluation is carried out by comparing the three proposed algorithms among themselves by applying the Wilcoxon test, and as a result, the best algorithm is determined as MPW-WOA. The proposed algorithms are compared with WOA and shown to be superior. The results of the best algorithm are compared with the methods in the literature, and it is superior in 16 out of 23 functions. This success is also confirmed by the Friedman test. Furthermore, the three proposed algorithms have been successfully applied to four real-world engineering problems, and especially MPW-WOA has produced the best or competitive results compared to its competitors. The overall evaluations have shown that this algorithm is an effective and promising alternative for many optimization problems.
Yazarlar (2)
1
Onur Inan
2
Sema Servi
Anahtar Kelimeler
Benchmark functions
Engineering problem
Optimization problems
WOA
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Arabian Journal for Science and Engineering
Q1
SJR Skoru0,545
H-Index89
ÜlkeGermany
Multidisciplinary (Q1)
Metrikler
3
Atıf
2
Yazar
4
Anahtar Kelime