Design and Profit Allocation in Two-Echelon Heterogeneous Cooperative Logistics Network Optimization by Yong Wang, Yingying Yuan, Kevin Assogba, Ke Gong, Haizhong Wang, Maozeng Xu, Yinhai Wang

“…First, a mixed integer linear programing model is introduced to minimize the total operating cost of nonempty coalitions. Thus, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm are hybridized to propose GA-PSO heuristics. …”
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Exploring the Orca Predation Algorithm for Economic Dispatch Optimization in Power Systems by Vivi Aida Fitria, Arif Nur Afandi, Aripriharta

“…This research shows that Orca Predation Algorithm consistently does better than other bio-inspired algorithms like Particle Swarm Optimization, Whale Optimization Algorithm, Grey Wolf Optimizer, the Bat Algorithm, Genetic Algorithm and Ant Colony Optimization in terms of minimum cost, average cost, and solution stability. …”
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Enhancing Pan evaporation predictions: Accuracy and uncertainty in hybrid machine learning models by Khabat Khosravi, Aitazaz A. Farooque, Amir Naghibi, Salim Heddam, Ahmad Sharafati, Javad Hatamiafkoueieh, Soroush Abolfathi

“…The models investigated include M5 Prime (M5P), M5Rule (M5R), Kstar, as well as their hybridized versions employing Bagging (BA), the adaptive neuro-fuzzy inference system (ANFIS), ANFIS-GA (genetic algorithm), and long short-term memory (LSTM) networks. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. …”
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An efficient binary spider wasp optimizer for multi-dimensional knapsack instances: experimental validation and analysis by Mohamed Abdel-Basset, Reda Mohamed, Karam M. Sallam, Ibrahim Alrashdi, Ibrahim A. Hameed

“…The experimental findings demonstrate that BSWO-RO4 can achieve exceptional results for the small and medium-scale instances, while the genetic algorithm integrated with RO4 can be superior for the large-scale instances. …”
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Construction and application of a physically-based constitutive model for superplastic deformation of near-α TNW700 titanium alloy by Lixia Ma, Dingyong He, Bangjian Yang, Xiuquan Han, Jichun Zhang, Weidong Li

“…Material constants are calibrated using a genetic algorithm combined with multi-objective optimization. …”
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Optimized Adaptive Neuro-Fuzzy Inference System Using Metaheuristic Algorithms: Application of Shield Tunnelling Ground Surface Settlement Prediction by Xinni Liu, Sadaam Hadee Hussein, Kamarul Hawari Ghazali, Tran Minh Tung, Zaher Mundher Yaseen

“…The predictive models were various nature-inspired frameworks, such as differential evolution (DE), particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimizer (ACO) to tune the adaptive neuro-fuzzy inference system (ANFIS). …”
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An improved SPWM control approach with aid of ant lion optimization for minimizing the THD in multilevel inverters by Alaa M. Abdel-hamed, Abdelrahman M. Nasser, Hamdy Shatla, Amr Refky

“…For verification, the performance and effectiveness of the ALO technique are assessed by comparing its results to those obtained using the simplified sinusoidal pulse width modulation (SSPWM) technique, genetic algorithm (GA), and particle swarm optimization (PSO) in existing literature. …”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…The meta-heuristic algorithms employed for fine-tuning the ANN's weight and bias parameters include the Genetic Algorithm (GA), Multi-Verse Optimizer (MVO), Moth Flame Optimization (MFO), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Advanced Grey Wolf Optimizer (AGWO), Biogeography-Based Optimization (BBO), and Particle Swarm Optimization with Grey Wolf Optimizer (PSOGWO). …”
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Modeling, evaluation and forecasting of suspended sediment load in Kal-e Shur River, Sabzevar Basin, in northeast of Iran by M. A. Zangeneh Asadi, L. Goli Mokhtari, R. Zandi, M. Naemitabar

“…The study employs ensemble Bagging algorithms, the gradient boosting machine (GBM), genetic algorithm, Naïve Bayes algorithm, gradient boosting decision trees, and extremely randomized trees. …”
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Study on an Intelligent Prediction Method of Ticket Price in a Subway System with Public-Private Partnership by Shengmin Wang, Jun Fang, Lanjun Liu, Han Wu

“…Compared with other prediction methods (the price adjustment method based on PPP contract, the traditional BP algorithm, the BP neural network improved by the genetic algorithm, the BP algorithm improved by the particle swarm optimization, and the support vector machine), the model proposed in this paper showed better prediction accuracy and calculation stability.…”
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Multiplex Community Detection in Social Networks Using a Chaos-Based Hybrid Evolutionary Approach by Bagher Zarei, Bahman Arasteh, Mehdi Asadi, Vahid Majidnezhad, Saeid Taghavi Afshord, Asgarali Bouyer

“…In the community structure detection phase, the community structure of the resulting weighted monoplex network is determined using the Improved Genetic Algorithm (IGA). The main aspects that differentiate IGA from other algorithms presented in the literature are as follows: (a) instead of randomly generating the initial population, it is smartly generated using the concept of diffusion. …”
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Predicting Compressive Strength of Concrete Containing Industrial Waste Materials: Novel and Hybrid Machine Learning Model by Mohammed Majeed Hameed, Mustafa Abbas Abed, Nadhir Al-Ansari, Mohamed Khalid Alomar

“…Since the traditional method of calculation CS is complicated and requires lots of effort, this article presents new predictive models called SVR−PSO and SVR−GA, that are a hybridization of support vector regression (SVR) with improved particle swarm algorithm (PSO) and genetic algorithm (GA). Furthermore, the hybrid models (i.e., SVR−PSO and SVR−GA) were used for the first time to predict CS of concrete where the cement component is partially replaced. …”
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The Prediction of Metro Shield Construction Cost Based on a Backpropagation Neural Network Improved by Quantum Particle Swarm Optimization by Lanjun Liu, Denghui Liu, Han Wu, Xinyu Wang

“…The determination coefficient, mean absolute percentage error, root mean square error, and mean absolute error, which are frequently used error analysis tools, were used to analyse the calculation errors of different models (the proposed model, a multiple regression method, a traditional BP model, a BP model optimized by the genetic algorithm, and the BP model optimized by the particle swarm optimization). …”
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Integrated Planning for Shared Electric Vehicle System Considering Carbon Emission Reduction by Xiaohui Sun, Yumei Mi, Askar Ahtam, Zhi Zuo

“…By applying these models to the Chicago Sketch network and using a genetic algorithm to solve the models, it is concluded that the optimal outlet location solution considering carbon emission reduction will increase the outlet construction cost and user travel time cost. …”
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Multiobjective Optimization of Surface Roughness and Tool Wear in High-Speed Milling of AA6061 by Machine Learning and NSGA-II by Anh-Tu Nguyen, Van-Hai Nguyen, Tien-Thinh Le, Nhu-Tung Nguyen

“…We applied a two-pronged approach that combines machine learning (ML) and a Nondominated Sorting Genetic Algorithm (NSGA-II) to model and optimize Ra and Vbmax. …”
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A New Mathematical Model for Cell Layout Problem considering Rotation of Unequal Dimensions of Cells and Machines by Raheleh Alamiparvin, Esmaeil Mehdizadeh, Hamed Soleimani

“…In large dimensions, 30 random problems were created, and the results of ICA were compared with the results of the particle swarm optimization (PSO) algorithm and genetic algorithm (GA). Finally, the parameters of the three meta-heuristic algorithms were set by the Taguchi method. …”
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Wind Energy Resource Prediction and Optimal Storage Sizing to Guarantee Dispatchability: A Case Study in the Kenyan Power Grid by Hampfrey Odero, Cyrus Wekesa, George Irungu

“…Therefore, this study aims to utilize backpropagation neural network (BPNN) algorithm to conduct hourly prediction of the generation output of Lake Turkana Wind Power Plant (LTWPP), a 310 MW plant connected to the Kenyan power grid, and optimally size its battery energy storage system (BESS) using genetic algorithm (GA) to guarantee its dispatchability. …”
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Presentating a multi-objective optimization model for resource-constrained project scheduling regarding financial costs, time delays and the reliability function by Saeideh Naderi, Mohsen Vaez-Ghasemi, Farzad Movahedi Sobhani

“…The results of using these algorithms and the statistical analysis (with 95% reliability) indicated that the performance was suitable for the Genetic Algorithm (GA). The calculation error between the Exact method and the meta-heuristic method for the three target categories of total cost, time delay, and reliability was calculated based on the obtained results. …”
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Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

“…The results predicted by the trained IPSO-BP neural network on 10 groups of test data are compared with the actual values, and the results predicted by BP model and genetic algorithm-BP (GA-BP) model are compared. The IPSO-BP model has the highest fitting accuracy. …”
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