Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms by Zhongqiang Ma (13765801)

“…The performance of all 15 of the algorithms is likely to deteriorate due to certain transformations, while the 4 state-of-the-art metaheuristics are less affected by transformations such as the shifting of the global optimal point away from the center of the search space. …”

Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog... by Mutasim Baba, Fuad

“…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. …”
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Seasonal variations in feed-water chemistry and fouling dynamics of reverse-osmosis systems: A global climate lens by Nasser Zareei (22921226)

Parametric Design Optimization in Sustainable Urban Design: In Hot Climate by Musleh, Mousa A. M.

“…This research employs Genetic algorithms as the computational design methodology to achieve parametric design optimization to design for a more sustainable cities and urban. …”
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Hybrid Bio-Inspired Routing Algorithms for Scalable and Adaptive Wireless Ad Hoc Networks by Santhosh Kumar, C.

“…In order to overcome such drawbacks, this paper has suggested a new hybrid bio-inspired routing protocol which combines the locally adaptive behav-ior characteristic of the Ant Colony Optimization (ACO) and the globally convergent efficiency of the Particle Swarm Optimization (PSO). …”
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An enhanced binary artificial rabbits optimization for feature selection in medical diagnosis by Al-Betar, Mohammed Azmi

“…ARO is a recent swarm-based optimization algorithm that mimics rabbits’ natural survival tactics and eating habits. …”
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A multi-objective planning approach for optimal DG allocation for droop based microgrids by Shaaban, Mostafa

“…The proposed formulation is compared to existing planning algorithms for droop-based microgrids. The re-sults show that including the secondary control region in the optimization problem achieves lower volt-age deviations and no frequency deviations at all demand levels. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

“…The results show an optimum resource allocation with an information-based cost function that is optimized by an Auction Algorithm.…”
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Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective by Mir, Imran

“…This study proposes an adaptable, bio-inspired optimization algorithm for Multi-Agent Space Exploration. …”
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Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization by Hafez, Ishaq

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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…Graph neural networks lower prediction error by up to thirty percent relative to descriptor-driven QSAR models for structurally diverse inhibitors. …”

Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints by Bashar Hassna (19170940)

“…This study presents a comprehensive analysis of the impact of climate change on global food systems, focusing on the risk assessment and optimization of food supply chains from the perspective of importers. …”

Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace by Shahid, Saif Mohammad

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Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…Our algorithm performs better than previous algorithms by finding lower energy structures or by performing fewer numbers of energy evaluations.…”
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A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability by Debabrata Mazumdar (18560506)

“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”

An Energy Efficient Wireless Sensor Network for Optimal Routing using Hybridized Bio-Inspired Technique by Askarovich, Ulashev Hubbim

“…While clustering techniques, such as Low Energy Adaptive Clustering Hierarchy (LEACH), help reduce energy usage, they suffer from inefficient local searches and poor exploration-exploitation balance.To address these limitations, this study proposes a hybrid bio-inspired optimization technique—Modified Harmony Search Algorithm (MHSA) combined with Competitive Swarm Optimization (CSO)—for optimal cluster head (CH) selection. …”
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Energy conversion of heat from abandoned oil wells to mechanical refrigeration - Transient analysis and optimization by Mohammed Al-Khawaja (17093017)

“…Using the genetic algorithm optimization method with R1234ze(E) as working fluid in both power and cooling loops, a maximum power loop efficiency of 6.3% and COP of 5.3 were obtained at a high pressure of 29 bar (in the power loop) with minimal expander diameter of 64, compressor diameter of 171 mm, and 18 expander-compressor units.…”

ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

“…The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. …”

A Comprehensive Framework for Optimizing and Integrating Electric Bus Service with Smart Grids for Sustainable Public Transportation by AlAli, Aisha Abdalla

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YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam (22330264)

“…Secondly, a Normalized Attention Mechanism (NAM) is introduced to optimize attention toward dense ship targets by merging contextual cues with global interdependencies. …”