Search Results - (( software optimization _ algorithm ) OR ( parallel optimisation based algorithm ))
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Tool path generation of contour parallel based on ant colony optimisation
Published 2016“…The optimisation of tool path length based on ACO algorithm ascertained that the cutting tool remove the uncut line once and able to eliminate the uncut region in the shortest tool path length. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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An adaptive flower pollination algorithm for minimizing software testing redundancy
Published 2017“…In this paper, we present an adaptive flower pollination algorithm for solving an optimization problem, i.e., minimization of software testing redundancy. …”
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A comparative study on testing optimization techniques with combinatorial interaction testing for optimizing software product line testing
Published 2025“…An experiment has been conducted on the most commonly used optimization algorithms in previous studies. The optimization algorithms we explored are the Genetic Algorithm, Cuckoo Search algorithm, Ant Colony algorithm, and Particle Swarm Optimization algorithm. …”
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Development of New Genetic Algorithm Software for Blow Mould Process
Published 2008“…The approach is based on newly development of Genetic Algorithm software. In this work, the objectives were to optimized parameters with newly develop software and compare with statistical software. …”
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks
Published 2016“…The results of this research are important in developing a routing algorithm for CHR6o3.…”
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Towards Software Product Lines Optimization Using Evolutionary Algorithms
Published 2019“…This research provides a framework to compare the performance of different multi-objective Evolutionary Algorithms in software product line context. We report on the problem encoding, variation operators and different types of algorithms: Indicator Based Evolutionary Algorithm (IBEA), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithms based on Decomposition (MOEA/D) and Strength Pareto Evolutionary algorithm II (SPEA-II). …”
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Particle swarm optimization (PSO) for CNC route problem
Published 2002“…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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Undergraduates Project Papers -
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Maintain optimal configurations for large configurable systems using multi-objective optimization
Published 2022“…Hence, multiobjective evolutionary algorithms help to optimize the configuration process of SPL. …”
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Multiobjective evolutionary algorithms NSGA-II and NSGA-III for software product lines testing optimization
Published 2020“…Hence, the testing process of SPL can utilize a multi-objective optimization algorithm to optimize the testing process. …”
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Proceeding Paper -
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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A kidney algorithm with elitism for combinatorial testing problem
Published 2020“…Kidney algorithm (KA) is a recent computational AI algorithm with sufficient optimization capability which outperforms the other AI algorithms (such as Genetic Algorithm (GA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), Harmony Search (HS)) from some aspects. …”
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Optimization of mycelium growth using genetic algorithm for multi-objective functions
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Undergraduates Project Papers -
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An improved genetic bat algorithm for unconstrained global optimization problems
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Software module clustering based on the fuzzy adaptive teaching learning based optimization algorithm
Published 2019“…Although showing competitive performances in many real-world optimization problems, Teaching Learning based Optimization Algorithm (TLBO) has been criticized for having poor control on exploration and exploitation. …”
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