Search Results - (( based evaluation study algorithm ) OR ( using optimization _ algorithm ))
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1
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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2
Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…These three combinatorial SKF algorithms use binary encoding to represent the solution to a combinatorial optimization problem. …”
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3
Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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4
A comparative study on ant-colony algorithm and genetic algorithm for mobile robot planning.
Published 2024“…Focusing on routing optimization, the study evaluates Ant-Colony Optimization (ACO) and Genetic Algorithm (GA) in Mobile Robot Planning. …”
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5
A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints
Published 2016“…Practically allevolutionary optimization studies have focused exclusively on the use of number of fitness evaluations as the constraining factor when comparing different evolutionary algorithms (EAs). …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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8
Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm
Published 2022“…In this study, a new proposed hybrid optimization algorithm, called Extended Bat Algorithm (EBA) is used for optimizing the PID controller for the wheel mobile robot. …”
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10
Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems
Published 2012“…Two versions of VEGSA algorithm are presented in this study. Convex and non-convex test functions on biobjective optimization problems are used to evaluate the effectiveness of the proposed VEGSA.…”
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11
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy
Published 2014“…A new approach of CS and WDO algorithm is used for selection of optimal threshold value. …”
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12
Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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Evaluation of fast evolutionary programming, firefly algorithm and mutate-cuckoo search algorithm in single-objective optimization / Muhammad Zakyizzuddin Rosselan, Shahril Irwan S...
Published 2016“…In this study proposes an evaluation of different computational intelligences, i.e Fast-Evolutionary Algorithm (FEP), Firefly Algorithm (FA) and Mutate-cuckoo Search Algorithm (MCSA) for solving single-objective optimization problem. …”
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14
Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Published 2025“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…For optimum results in performance analysis, the optimal value of the MOPSO-CD was evaluated using (ZDT), (WFG), and (DTLZ) with two or three objectives over D2MOPSO, AgMOPSO, MMOPSO, and EMOSO algorithms. …”
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16
Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…To evaluate the performance of the proposed IBOA training method, the obtained results are compared to the results of the momentum backpropagation (MBP), the particle swarm optimization (PSO) and the standard butterfly optimization algorithm (BOA) training methods. …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…The proposed Hybrid Sentiment-based Support Vector Machine with a Whale Optimization Algorithm (SVMWOA). will be evaluated and compared based on performance measures. …”
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Proceeding Paper -
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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector
Published 2025“…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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An experimental study of modified black hole algorithms
Published 2018“…The BH algorithm is a population-based method which uses more than one agent to find a solution in a search space. …”
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