A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch by Abido, A.A.

“…A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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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. The calibrated simulation model based on indoor and outdoor measured temperature for a school of interest is used to evaluate the optimization strategies. …”
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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”

Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

“…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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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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Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study by Abido, M.A.

“…Specifically, Niched Pareto genetic algorithm (NPGA), nondominated sorting genetic algorithm (NSGA), and strength Pareto evolutionary algorithm (SPEA) have been developed and successfully applied to environmental/economic electric power dispatch (EED) problem. …”
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Heuristics. (c2006) by Kallab, Chadi

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Fuzzy simulated evolution for power and performance optimization ofVLSI placement by Sait, Sadiq M.

“…This is a hard multiobjective combinatorial optimization problem with no known exact and efficient algorithm that can guarantee finding a solution of specific or desirable quality. …”
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Energy removal in dynamical systems through an optimal sequence of constraint application by Issa, Jimmy

“…The optimization process is illustrated by means of simple mass-spring and membrane systems and the corresponding problems are solved using a genetic algorithm.…”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

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A modified optimal design of a vibration absorber for ground motion isolation by Issa, Jimmy S.

“…The first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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Combined cycle gas turbine system optimization for extended range electric vehicles by Barakat, Aya A.

“…The two-steps methodology consists of conducting first an exergo-technological analysis using a Non-dominated Sorting Genetic Algorithm to identify the best suitable combined cycle configuration for integration in a series hybrid powertrain. …”
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Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints by Bashar Hassna (19170940)

“…Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …”

A hybrid model for the optimum integration of renewable technologies in power generation systems by Poullikkas, Andreas

“…The main purpose of this work is to assess the unavoidable increase in the cost of electricity of a generation system by the integration of the necessary renewable energy sources for power generation (RES-E) technologies in order for the European Union Member States to achieve their national RES energy target. The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. …”
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Shape and sizing optimisation of space truss structures using a new cooperative coevolutionary-based algorithm by Dehkordi, Amin Abdollahi

“…This novel alternative optimisation strategy (CCMPA-GS) compared with 13 established genetic, evolutionary, swarm, and memetic meta-heuristic optimisation algorithms. …”
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LOCATING DAMAGES IN THIN ALUMINIUM PLATES USING LAMB WAVES AND AGENETIC OPTIMIZATION APPROACH by A. Masurkar, Faeez

“…The damage locations are further optimized within the enclosed area using the GO algorithm. …”
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Mobile Energy Storage Systems for Benefit Maximization in Resilient Smart Grids by Alshaal, Dima

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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…We compare our models to others constructed using other well established techniques such as C4.5, Genetic Algorithms, Simulated Annealing, Tabu Search, multi-layer perceptron with back-propagation, multi-layer perceptron hybridized with ABC and the majority classifier. …”
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