Search Results - (( java application optimization algorithm ) OR ( set optimization strategy algorithm ))
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Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
Published 2017“…This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines
Published 2009“…It confirms that the proposed genetic algorithm procedure is able to tackle the problem complexity and reach to optimal solutions in different production strategies. …”
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Thesis -
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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A swarm intelligent approach for multi-objective optimization of compact heat exchangers
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support
Published 2019“…The output of PhABC is a set of promising optimal test set combinations. …”
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PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support
Published 2019“…The output of PhABC is a set of promising optimal test set combinations. …”
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Assessing optimization based strategies for t-way test suite generation: The case for flower-based strategy
Published 2016“…In order to summarize the achievements so far and facilitate future development, the main focus of this paper is, first, to present a critical comparison of adoption optimization algorithms (OA) as a basis of the t-way test suite generation strategy and, second, to propose a new t-way strategy based on Flower Pollination Algorithm, called Flower Strategy (FS). …”
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Exponentially adaptive sine-cosine algorithm for global optimization
Published 2019“…Sine-Cosine algorithm (SCA) is an optimization algorithm formulated based on mathematical Sine and Cosine terms. …”
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Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing
Published 2017“…Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. …”
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