Search Results - (( using optimization problems algorithm ) OR ( using function search algorithm ))

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  1. 1

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…Later, this algorithm was used to solve bi-objective Production Planning (PP) and Scheduling Problem (Sch.P). …”
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    Thesis
  2. 2

    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

    Published 2012
    “…This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. …”
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  3. 3

    A novel explanatory hybrid artificial bee colony algorithm for numerical function optimization by Jarrah, Muath Ibrahim, Mohamad Jaya, Abdul Syukor, Mohd Abid, Mohd Asyadi Azam, Alqattan, Zakaria N., Azam, Mohd Asyadi, Abdullah, Rosni, Jarrah, Hazim, Abu‑Khadrah, Ahmed Ismail

    Published 2020
    “…Therefore, researchers extensively try to improve methods of solving complex optimization problems. Many SI search algorithms are widely applied to solve such problems. …”
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    Article
  4. 4

    Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy by Bhandari, A.K., Singh, V.K, Kumar, A., Singh, G.K.

    Published 2014
    “…To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoo search (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur’s entropy has been employed. …”
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    Article
  5. 5

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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  6. 6

    Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

    Published 2018
    “…Firefly algorithm (FA) is a newly introduced meta-heuristic, nature-inspired, stochastic algorithm for solving various types of optimization problems. …”
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    Article
  7. 7

    Ringed seal search for global optimization via a sensitive search model / Younes Saadi by Younes, Saadi

    Published 2018
    “…The quality of the algorithm is comprehensively evaluated on various standard benchmark test functions using variety of quality metrics and using three baseline algorithms for comparison. …”
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    Thesis
  8. 8

    Hybrid harmony search algorithm for continuous optimization problems by Ala’a Atallah, Hamad Alomoush

    Published 2020
    “…Harmony Search (HS) algorithm has been extensively adopted in the literature to address optimization problems in many different fields, such as industrial design, civil engineering, electrical and mechanical engineering problems. …”
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  9. 9

    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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    Enhancing the cuckoo search with levy flight through population estimation by Mohd Nawi, Nazri, Shahuddin, Shah Liyana, Rehman, Muhammad Zubair, Khan, Abdullah

    Published 2016
    “…This paper proposed the use of population estimation in a new meta-heuristic called Cuckoo search (CS) algorithm to minimize the training error, achieve fast convergence rate and to avoid local minimum problem. …”
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    Article
  13. 13

    A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem by Ong, Kok Meng

    Published 2021
    “…Hence, using an effective optimiser to solve these problems with high complexity is important. …”
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  14. 14

    A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

    Published 2022
    “…Due to the limitation of the SKF algorithm which only able to operate in continuous search space, the proposed algorithm makes use of a new interpretation that incorporates mutation and Hamming distance, allowing the proposed algorithm to function in discrete search space. …”
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    Extended Bat Algorithm (EBA) as an improved searching optimization algorithm by Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Nor Rul Hasma, Abdullah, Zainah, Md. Zain, Indra, Riyanto

    Published 2018
    “…This paper presents a new searching technique by using a new variant of Bat Algorithm (BA) known as Extended Bat Algorithm (EBA). …”
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    Book Chapter
  18. 18

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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  19. 19

    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

    Published 2022
    “…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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    Conference or Workshop Item
  20. 20

    An improved artificial immune system based on antibody remainder method for mathematical function optimization by Yap D.F.W., Habibullah A., Koh S.P., Tiong S.K.

    Published 2023
    “…Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. …”
    Conference paper