ArticleScientific reports2023
A new bio-inspired metaheuristic algorithm for solving optimization problems based on walruses behavior.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed.
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- Solid oxide fuel cell simulation model tuning using operating conditions dependent optimization techniques.Scientific reports · 2026Article
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- Optimized model of microbial fuel cell using AI-driven walrus optimization algorithm.Scientific reports · 2026Article
- Hexa classification of erythemato-squamous disease using deep dual features-based neural network.Postepy dermatologii i alergologii · 2026Article
- An Improved Whale Migration Optimization Algorithm for Cooperative UAV 3D Path Planning.Biomimetics (Basel, Switzerland) · 2025Article
- An Improved Greater Cane Rat Algorithm with Adaptive and Global-Guided Mechanisms for Solving Real-World Engineering Problems.Biomimetics (Basel, Switzerland) · 2025Article
- Multi-Strategy Improved Red-Billed Blue Magpie Optimization Algorithm and Its Applications.Biomimetics (Basel, Switzerland) · 2025Article
- Enhanced secretary bird optimization algorithm with multi-strategy fusion and Cauchy-Gaussian crossover.Scientific reports · 2025Article
- Non-proliferative diabetic retinopathy detection using Rosmarus Quagga optimized explainable generative meta learning based deep convolutional neural network model.International ophthalmology · 2025Article
- An enhanced walrus optimization algorithm for flexible job shop scheduling with parallel batch processing operation.Scientific reports · 2025Article
- Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women.Sensors (Basel, Switzerland) · 2025Article
- Optimal scheduling and energy management of a multi-energy microgrid with electric vehicles incorporating decision making approach and demand response.Scientific reports · 2025Article
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2 authors.
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Abstract
This paper introduces a new bio-inspired metaheuristic algorithm called Walrus Optimization Algorithm (WaOA), which mimics walrus behaviors in nature. The fundamental inspirations employed in WaOA design are the process of feeding, migrating, escaping, and fighting predators. The WaOA implementation steps are mathematically modeled in three phases exploration, migration, and exploitation. Sixty-eight standard benchmark functions consisting of unimodal, high-dimensional multimodal, fixed-dimensional multimodal, CEC 2015 test suite, and CEC 2017 test suite are employed to evaluate WaOA performance in optimization applications. The optimization results of unimodal functions indicate the exploitation ability of WaOA, the optimization results of multimodal functions indicate the exploration ability of WaOA, and the optimization results of CEC 2015 and CEC 2017 test suites indicate the high ability of WaOA in balancing exploration and exploitation during the search process. The performance of WaOA is compared with the results of ten well-known metaheuristic algorithms. The results of the simulations demonstrate that WaOA, due to its excellent ability to balance exploration and exploitation, and its capacity to deliver superior results for most of the benchmark functions, has exhibited a remarkably competitive and superior performance in contrast to other comparable algorithms. In addition, the use of WaOA in addressing four design engineering issues and twenty-two real-world optimization problems from the CEC 2011 test suite demonstrates the apparent effectiveness of WaOA in real-world applications. The MATLAB codes of WaOA are available in https://uk.mathworks.com/matlabcentral/profile/authors/13903104 .
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