Search Results - (( developing continuous optimization algorithm ) OR ( based optimization based algorithm ))
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1
Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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2
Review of Multi-Objective Swarm Intelligence Optimization Algorithms
Published 2021“…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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4
A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…In this research, a novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people was developed, it is called ‘‘Nomadic People Optimizer (NPO)’’. …”
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Computational intelligence based power tracing for nondiscriminatory losses charge allocation and voltage stability improvement. / Zulkifli Abdul Hamid
Published 2013“…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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Web-Based Route Optimization System For Logistic Using Agglomerative Clustering And Genetic Algorithm
Published 2020“…This system will first cluster those addresses based on the number of trucks involved and then perform the route optimization algorithm to suggest the shortest route to the user. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Shark Smell Optimization (SSO) algorithm has been proven to have high efficiency in many optimization applications. …”
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Genetic-local hybrid optimizer for solving advance layout problem
Published 2006“…Results are achieved through the use of local optimizer, separation algorithm with genetic algorithm also called hybrid simple genetic. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…This paper presents the identification of double pendulum overhead crane (DPOC) plant based on the hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (HMVOSCA) using the continuous-time Hammerstein model. …”
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Improvement and application of particle swarm optimization algorithm
Published 2025“…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm
Published 2016“…This project develops a novel strategy to minimize the test consideration using the Particle Swarm Optimization and the Bat Algorithm.…”
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Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem
Published 2015“…Viewing as optimization problem and focusing on two machines, this research aims to develop a new Simulated Annealing based scheduling algorithm, called SA2M, for flow shop problem. …”
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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14
Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid
Published 2013“…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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15
Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid
Published 2013“…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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Thesis -
16
Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
Published 2022“…Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. …”
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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19
Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…The objectives of this research are to develop an algorithm for integrated scheduling and conflict-free routing of jobs and AGVs in FMS environment using a hybrid genetic algorithm, ensure the algorithm validity and improvement on the performance of the developed algorithm. …”
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20
Green network planning and operational power consumption optimization in LTE-A using artificial intelligence
Published 2015“…The second stage of the developed algorithm optimizes the average number of relay station per base station and their distance from the respective base station to meet the capacity constraint of the network operator. …”
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