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  1. 1
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    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
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  2. 2
    A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem

    A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem by Nurul Asyikin, Zainal, Kamal Z., Zamli, Fakhrud, Din

    Published 2020
    “…As such, the adoption of parameter free meta-heuristic algorithms is often straightforward. …”
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  3. 3
    Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model

    Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

    Published 2018
    “…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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  4. 4
    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. …”
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  5. 5
    Evaluation of outlier filtering algorithms for accurate measurement of travel time reliability incorporating lane-splitting situations / Obada M. A. Asqool

    Evaluation of outlier filtering algorithms for accurate measurement of travel time reliability incorporating lane-splitting situations / Obada M. A. Asqool by Obada , M. A. Asqool

    Published 2022
    “…The parameters of the Jang algorithm and TransGuide algorithm were sensitive for different days. …”
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  6. 6
    Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model

    Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model by Azrag, Mohammed Adam Kunna, Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

    Published 2018
    “…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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  7. 7
    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems

    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

    Published 2018
    “…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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  8. 8
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  9. 9
    An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite

    An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

    Published 2018
    “…In line with such a need, this paper presents a unified strategy based on the new meta-heuristic algorithm, called the elitist flower pollination algorithm (eFPA), for sequence and sequence-less coverage. …”
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  10. 10
    Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria

    Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

    Published 2021
    “…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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  11. 11
    Modified Parameters of Harmony Search Algorithm for Better Searching

    Modified Parameters of Harmony Search Algorithm for Better Searching by Nur Farraliza, Mansor, Abas, Z.A, Shibghatullah, A.S., Rahman, A.F.N.A

    Published 2017
    “…The latest approaches still unable to address the fairness problem that has emerged, thus this research proposes a strategy to adopt an amendment of a harmony search algorithm in order to address the fairness issue and thus the level of fairness will be escalate. …”
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  12. 12
    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    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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  13. 13
    Adopting Jaya Algorithm for Team Formation Problem

    Adopting Jaya Algorithm for Team Formation Problem by Kader, Md. Abdul, Kamal Z., Zamli

    Published 2020
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  14. 14
    Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria

    Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

    Published 2021
    “…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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  15. 15
    Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-way Testing

    Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-way Testing by Muazu, A.A., Hashim, A.S., Sarlan, A.

    Published 2022
    “…Thus, we found that all metaheuristics has a simple structure to be adopted in different areas for becoming a more efficient in optimization. …”
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  16. 16
    An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis

    An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

    Published 2022
    “…However, different clustering algorithms have different parameters that need to be specified. …”
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  17. 17
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  18. 18
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  19. 19
    Weighting method for modal parameter based damage detection algorithms

    Weighting method for modal parameter based damage detection algorithms by Fayyadh, M.M., Abdul Razak, H.

    Published 2011
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  20. 20
    On determination of input parameters of the mass transfer process by fuzzy approach.

    On determination of input parameters of the mass transfer process by fuzzy approach. by Maan, Normah, Talib, Jamalludin, Arshad, Khairil Annuar, Ahmad, Tahir

    Published 2005
    “…The algorithm is also capable of determining the optimal values of the input parameters. …”
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