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    Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2026
    “…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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    Book
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    Mobile game application development using evolutionary algorithms by Ong, Jia Hui

    Published 2014
    “…Evolutionary Programming (EP) is used as the main evolutionary technique in this study. …”
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    Thesis
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    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
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    Enhancing benchmark optimization with evolutionary random approach: A comparative analysis of modified adaptive bats sonar algorithm (MABSA) by Nor Shuhada, Ibrahim, Nafrizuan, Mat Yahya, Saiful Bahri, Mohamed, Mohd Ismail, Yusof

    Published 2025
    “…Recently, evolutionary algorithms have emerged as powerful tools for solving complex optimization problems across various domains. …”
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    Conference or Workshop Item
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    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

    Published 2025
    “…Among these algorithms, metaheuristics are an appropriate tool to solve these real problems. …”
    Article
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    A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

    Published 2016
    “…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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    Article
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    Automatic generation of mobile content in entertainment applications using evolutionary computing by Teo, Jason Tze Wi, Chin, Kim On, Rayner Alfred, Ong Jia Hui

    Published 2010
    “…Evolutionary Programming is used as the main evolutionary technique in this study. …”
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    Research Report
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    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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    Thesis
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    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The combined influence of the genetic algorithm and correlation analysis are used in this technique. …”
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    Article
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    Early explorations of EEG as a method for interactive evolutionary design of 3-dimensional objects by Chew, Lin Hou, James Mountstephens, Teo, Jason Tze Wi

    Published 2015
    “…This paper introduces an automatic method for generation of 3D artforms using electroencephalogram (EEG). Interactive evolutionary computing (IEC) is the typical method used to evolve art, however, IEC is often reported to cause significant fatigue among its users due to its repetitive and time-consuming characteristics. …”
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    Article
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    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
    “…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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    Journal
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    Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin by Mohd Zainol Abidin, Nor Syakila

    Published 2014
    “…In the proposed MLFNN, Firefly Algorithm (FA) was employed as the optimizer and search tools of the MLFNN training parameters. …”
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    Article
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