Search Results - (( using optimization strategy algorithm ) OR ( data optimization based algorithm ))
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1
Whale optimization algorithm strategies for higher interaction strength t-way testing
Published 2022“…To ensure that WOA conquers premature convergence and avoids local optima for large search spaces (owing to high-order interaction), three variants of WOA have been developed, namely Structurally Modified Whale Optimization Algorithm (SWOA), Tolerance Whale Optimization Algorithm (TWOA), and Tolerance Structurally Modified Whale Optimization Algorithm (TSWOA). …”
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2
A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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3
Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. …”
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4
Balancing exploration and exploitation in ACS algorithms for data clustering
Published 2019“…Ant colony optimization (ACO) is a swarm algorithm inspired by different behaviors of ants. …”
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5
Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm
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6
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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7
Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator
Published 2019“…Being a NP-complete problem, pairwise test suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in the literature. …”
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8
Improvement DACS3 Searching Performance using Local Search
Published 2009“…Therefore this research aims to improve the algorithm using various supportive and improvement strategies. …”
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9
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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10
A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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11
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…In addition, the simulation random data for were used to solve single and bi-objective optimization PP and Sch.P to improve the validation and verify the performance of the proposed algorithms. …”
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12
Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation
Published 2018“…Many t-way test data generation strategies have been proposed in the literature to generate optimized t-way test data. …”
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13
Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation
Published 2020“…Addressing the aforementioned issues, this research proposes the development and implementation of hybrid t-way strategy based Migrating Birds Optimization Algorithm (MBO) and Genetic Algorithm (GA) with elitism, termed Elitist Hybrid MBO-GA. …”
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14
Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…In this research, we showed how evolutionary multi-objective algorithms can be used to solve the view selection problem and its advantage over classical optimization problems were described. …”
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15
Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).…”
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16
BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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18
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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19
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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20
Hybrid Henry Gas-Harris Hawks comprehensive-opposition algorithm for task scheduling in cloud computing
Published 2025“…This method is based on two elements: comprehensive opposition-based learning (COBL) and Harris Hawks Optimization (HHO). …”
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