Search Results - (( java application optimization algorithm ) OR ( set optimization strategy algorithm ))

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  1. 1

    Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

    Published 2017
    “…This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. …”
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    Article
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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    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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    Conference or Workshop Item
  4. 4

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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    Article
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    Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines by Noroziroshan, Alireza

    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 by Zulkifli, Abdul Hayy

    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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    Final Year Project
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    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Jason, Teo, Kim, On Chin, Alfred, Rayner

    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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    Article
  8. 8

    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Teo, Jason Tze Wi, Rayner Alfred, Kim, On Chin

    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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    Article
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    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    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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    Article
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    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…The output of PhABC is a set of promising optimal test set combinations. …”
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    Conference or Workshop Item
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    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…The output of PhABC is a set of promising optimal test set combinations. …”
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    Conference or Workshop Item
  16. 16

    Assessing optimization based strategies for t-way test suite generation: The case for flower-based strategy by Abdullah, Nasser, Sariera, Yazan A., Alsewari, Abdulrahman A., Kamal Z., Zamli

    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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  17. 17

    Exponentially adaptive sine-cosine algorithm for global optimization by Mohd Falfazli, Mat Jusof, Nurul Amira, Mhd Rizal, Ahmad Azwan, Abdul Razak, Shuhairie, Mohammad, Ahmad Nor Kasruddin, Nasir

    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 by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    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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    Article
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    Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing by Din, Fakhrud, Kamal Z., Zamli

    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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    Conference or Workshop Item
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