Search Results - (( problem implementation real algorithm ) OR ( parameter optimization based algorithm ))
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1
Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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2
Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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4
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The final problem is the ability of the algorithm to solve large-scale problems, which mostly are the real world problems. …”
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Optimization of balanced academic curriculum problem in educational institutions using teaching learning based optimization algorithm
Published 2025“…This study aims to optimize BACP using the Teaching-Learning Based Optimization (TLBO) algorithm, addressing the limitations of existing approaches and providing an efficient framework for curriculum balancing. …”
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The effect of job satisfaction on the relationship between organizational culture and organizational performance
Published 2023“…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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Parameter identification of solar cells using improved Archimedes Optimization Algorithm
Published 2023“…The parameters of solar cells for five PV models are identified using an Improved Archimedes Optimization Algorithm (IAOA) in this paper. …”
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Hybrid evolutionary optimization algorithms: A case study in manufacturing industry
Published 2014“…This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Then, timetabling process is performed to identify a set of departure times at both origin and destination based on predefined parameters. The multiobjective set covering model is used by including some real-world restrictions to find number of buses and drivers as it can represent the problem clearly for implementation. …”
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10
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…MPSO-HALS is implemented into low-cost microcontroller for real-time application. …”
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Using scatter search algorithm in implementing examination timetabling problem
Published 2023“…The study investigates the most suitable parameters of Scatter Search algorithm for the population based algorithm. …”
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…Finally, the proposed approach was implemented in a real-world problem for Baghdad Soft Drinks Company to automate their APP. …”
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13
Marine Predator Algorithm and Related Variants: A Systematic Review
Published 2025“…The algorithm is easy to implement and robust in searching, yielding better solutions to many real-world problems. …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…Performance indicators included the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Parameter Magnitude-based Information Criterion 2 (PMIC2). …”
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15
Marine Predator Algorithm and Related Variants: A Systematic Review
Published 2025“…The algorithm is easy to implement and robust in searching, yielding better solutions to many real-world problems. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid
Published 2023“…Initially, the Particle Swarm Optimization was implemented to establish the optimal sizes of DGs and the performance of the implemented algorithm was analyzed and quantified. …”
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…To verify the model, four examples from literature were considered and compared the MOGSA’s optimum solutions result by Genetic Algorithm’s (GA) result. The results obtained from problem were analyzed based on the objective function (cost), and the design parameters of the network. …”
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18
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…Hence, this research’s objective aimed to propose an optimization strategy based on Structural Modification and Optimizing Training Network for improving the lacking of accuracy of response in the chatbot application, to propose the algorithm enhancement to improve the current attention mechanism in the Attentive Sequence-to-Sequence model and the network’s training optimization of its inability to memorize the dialogue history, and lastly, to evaluate the accuracy of response of the proposed solution through data training on loss function and real data testing. …”
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Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System
Published 2020“…This research aimed to develop a Predictive Functional Control using Reduced-Order Observer (PFC-ROO) to reduce the complexity of the pneumatic system. An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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