Sustainable economic production quantity optimization (SEPQ) considering food waste emission and water waste emission using genetic algorithm by Windy Puspika, Ilyas Masudin, Thomy Eko Saputro, Salman Alfarisi, Dian Palupi Restuputri, S. Sarifah Radiah Shariff

“…This study presents a novel approach for optimizing Sustainable Economic Production Quantity (SEPQ) by incorporating food waste and water waste emissions into the production planning process through the use of a Genetic Algorithm (GA). …”
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Optimizing Autonomous Multi-UAV Path Planning for Inspection Missions: A Comparative Study of Genetic and Stochastic Hill Climbing Algorithms by Faten Aljalaud, Yousef Alohali

“…Efficient path planning is vital for multi-UAV inspection missions, yet the comparative effectiveness of different optimization strategies has not received much attention. …”
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Predicting CO₂ Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally, S. K. Towfek

“…In this paper, we propose a general framework that combines advanced deep learning models (such as GRU, Bidirectional GRU (BIGRU), Stacked GRU, and Attention-based BIGRU) with a novel hybridized optimization algorithm, GGBERO, which is a combination of Greylag Goose Optimization (GGO) and Al-Biruni Earth Radius (BER). …”
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Optimal Sizing of a Hybrid Renewable Energy System for Auxiliary Services in Substations Through Genetic Algorithm and Variable Neighborhood Search by Matheus Holzbach, John Fredy Franco Baquero, Mariana Resener

“…The results demonstrate that the proposed sizing approach successfully minimizes costs while ensuring reliability, highlighting its potential to optimize hybrid renewable backup systems for critical substation loads.…”
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Mexican axolotl optimization algorithm with a recalling enhanced recurrent neural network for modular multilevel inverter fed photovoltaic system by R. Madavan, B. Karthikeyan, R. Palanisamy, Mohammad Imtiyaz Gulbarga, Mohammed Al Awadh, Liew Tze Hui

“…Unlike traditional multilevel inverters (MLI), the MMI structure utilized in this work requires fewer power electronic components, reducing cost and complexity. The MAO algorithm optimally tunes control gain parameters offline, creating a dataset of optimal control signals, while the RERNN method predicts and applies real-time control signals, ensuring an efficient and stable power supply. …”
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Developing an Optimized Energy-Efficient Sustainable Building Design Model in an Arid and Semi-Arid Region: A Genetic Algorithm Approach by Ahmad Walid Ayoobi, Mehmet Inceoğlu

“…A comprehensive analysis and optimization model was developed using genetic algorithms to individually optimize various sustainable strategies. …”
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Cost-Based Optimal Allocation of Shunt Capacitors in Radial Distribution Networks Considering Load Types Using Crow Search Algorithm by Stephen W. Mathenge, Edwell. T. Mharakurwa, Lucas Mogaka

“…CSA’s performance was benchmarked against invasive weed optimization (IWO), teacher learner-based optimization (TLBO), and artificial bee colony (ABC) algorithms. …”
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Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms by Leta Daba Gemechu, Dame Alemayehu Efa, Robsan Abebe

“…Machine learning helps in predicting the optimal parameters, whereas nanofluids enhance cooling efficiency while preserving both the tool and the workpiece. …”
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Optimum design of double tuned mass dampers using multiple metaheuristic multi-objective optimization algorithms under seismic excitation by Fateme Zamani, Sayyed Hadi Alavi, Mohammadreza Mashayekhi, Ehsan Noroozinejad Farsangi, Ataallah Sadeghi-Movahhed, Ali Majdi

“…The tuning process is carried out using a combination of Pareto front derived from seven multi-objective metaheuristic optimization algorithms with two objectives. The proposed methodology is applied to a 10-floor case study, using ground acceleration time histories to evaluate its seismic performance. …”
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Optimization of a Navigation System for Autonomous Charging of Intelligent Vehicles Based on the Bidirectional A* Algorithm and YOLOv11n Model by Shengkun Liao, Lei Zhang, Yunli He, Junhui Zhang, Jinxu Sun

“…Aiming to enable intelligent vehicles to achieve autonomous charging under low-battery conditions, this paper presents a navigation system for autonomous charging that integrates an improved bidirectional A* algorithm for path planning and an optimized YOLOv11n model for visual recognition. …”
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A practical guide to optimizing industrial thermal spraying through comparative multi-objective optimization by Wolfgang Rannetbauer, Simon Hubmer, Carina Hambrock, Ronny Ramlau

“…This paper applies three multi-objective optimization algorithms to determine optimal process parameters for high-velocity oxygen fuel (HVOF) thermal spraying. …”
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Improved Particle Swarm Optimization with a Collective Local Unimodal Search for Continuous Optimization Problems by Martins Akugbe Arasomwan, Aderemi Oluyinka Adewumi

“…A new local search technique is proposed and used to improve the performance of particle swarm optimization algorithms by addressing the problem of premature convergence. …”
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Parameter extraction of PV models under varying meteorological conditions using a modified electric eel foraging optimization algorithm by Hadeer Khalifa, Mohamed Ebeed, Gaber Magdy, Sherif A. Khaleel, Mohamed I. Shehata, Moataz M. Salah, Francisco Jurado, Hossam Hassan Ali

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High-efficiency Axial Flow Fan Design by Combining Through-flow Modeling, Optimization Algorithm and Computational Fluid Dynamics Simulation by C. Lee, S. W. Kim, H. T. Byun, S. H. Yang

“…The optimization algorithm is applied to the fan design and through-flow analysis program, achieving a very fast and simple optimization process and obtaining the optimal axial fan model. …”
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Genetic algorithm optimization of ensemble learning approach for improved land cover and land use mapping: Application to Talassemtane National Park by Ali Azedou, Aouatif Amine, Isaya Kisekka, Said Lahssini

“…This study proposes a Genetic Algorithm (GA) optimization method for ensemble classification to improve LCLU classification accuracy while maintaining computational efficiency. …”
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A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters by Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu

“…This paper introduces a novel hyperparameter optimization framework for regression tasks called the Combined-Sampling Algorithm to Search the Optimized Hyperparameters (CASOH). …”
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Effects of optimized interaction of short-term hypergravity stimulation and nitrate-deficient cultivation in maize root using genetic-immunological algorithms by Ronnie Concepcion II, R-Jay Relano, Adrian Genevie Janairo, Kate Francisco, Lance Garcia, Hugo Montanvert

“…This study pioneered an experimental approach to address the challenges posed by nutrient deficiency in hydroponic environment by integrating Multigene Genetic Programming (MGGP) with immunological computation algorithms, namely Clonal Selection Algorithm (CSA), Ant Colony Optimization Algorithm (ACOA), and COVID Optimization Algorithm (COVIDOA) in determining the exact optimal time exposure to 2 g hypergravity that can induced the growth of three maize genotypes (PSB 92–97, NSIC CN 302, and NSIC CN 282). …”
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Advanced Cascaded Scheduling for Highly Autonomous Production Cells with Material Flow and Tool Lifetime Consideration using AGVs by Eddi Miller, Bastian Engelmann, Tobias Kaupp, Jan Schmitt

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Optimization model for reliability-based maintenance strategies of critical components in electric multiple units by CHEN Jiayu, SONG Dongli, GENG Fangdong

“…In addition, a parallel quantum genetic algorithm was incorporated to calculate parameters such as the optimal maintenance interval and reliability. …”
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Multi-Criteria Optimization of a Standalone Photovoltaic System in Cyprus (Techno-Economic Analysis) by Athina Vogiatzoglou, Konstantinos Alexakis, Dimitris Askounis

“…This study proposes a two-stage optimization approach for standalone photovoltaic systems, employing three distinct optimization algorithms—NSGA-II, DEMO, and Particle Swarm Optimization—to minimize both the Loss of Load Probability (LLP) and the life cycle cost (LCC). …”
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