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  1. 1
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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  2. 2
    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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  3. 3
    An empirical study of density and distribution functions for ant swarm optimized rough reducts

    An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…Ant colony approach in Ant Swarm algorithm generates local solutions which satisfy the Gaussian distribution for global optimization using PSO algorithm. …”
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  4. 4
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…DE has effectively solved various global optimization problems, including benchmark functions. …”
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  5. 5
    Chaos search in fourire amplitude sensitivity test

    Chaos search in fourire amplitude sensitivity test by Koda, Masato

    Published 2012
    “…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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  6. 6
    Chaos Search in Fourier Amplitude Sensitivity Test

    Chaos Search in Fourier Amplitude Sensitivity Test by Koda, Masato

    Published 2012
    “…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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  7. 7
    Optimization of supply chain management by simulation based RFID with XBEE Network

    Optimization of supply chain management by simulation based RFID with XBEE Network by Soomro, Aftab Ahmed

    Published 2015
    “…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. …”
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  8. 8
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…The discrete MOPSO also includes the modified maximin fitness function to promote solution diversity in the selection of global best solutions. …”
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  9. 9
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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  10. 10
    Discrete-time system identification using genetic algorithm with single parent-based mating technique

    Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

    Published 2024
    “…The successful validation in real-world systems marks a significant milestone, showing that the SPM technique can significantly improve model optimization in diverse and practical contexts . This research makes several important contributions to the field of GA and SI. …”
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  11. 11
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

    Published 2012
    “…A technique for obtaining globally optimal schedules for the flow of crude is developed. …”
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  12. 12
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan , Yin Keong

    Published 2009
    “…A technique for obtaining globally optimal schedules for the flow of crude is developed. …”
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  13. 13
    Efficient beamforming and spectral efficiency maximization in a joint transmission LTE-A system

    Efficient beamforming and spectral efficiency maximization in a joint transmission LTE-A system by Faisal, Ali Raed

    Published 2016
    “…As a contribution of this thesis, diversity loss can be solved by replacing the inactive particles adaptively based on the difference between local best and global best optimization criterion. …”
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  14. 14
    Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems

    Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems by Motwakel, Abdelwahed, Hassan Abdalla Hashim, Aisha, Mengash, Hanan Abdullah, Alruwais, Nuha, Yafoz, Ayman, Alsini, Raed, Edris, Alaa

    Published 2023
    “…Therefore, this study presents a new Green Anaconda Optimization Based Energy Aware Clustering Protocol (GAOB-EACP) approach for WSN. …”
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  15. 15
    Identification of debris flow initiation zones using topographic model and airborne laser scanning data

    Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

    Published 2017
    “…Conditioning parameters were numerically optimized to identify the arbitrarily maximum model basis function for eleven variables, using MARSplines analysis (algorithm). …”
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  16. 16
    Opposition-based Whale Optimization Algorithm

    Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

    Published 2018
    “…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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  17. 17
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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  18. 18
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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  19. 19
    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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  20. 20
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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