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A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408) by Woon, Siew Fang, Karim, Sharmila, Mohamad, Mohd Saiful Adli

“…At the initial stage, an auxiliary function is introduced in discrete filled function method which turns the local minimizer of the original function to be a local maximizer. …”
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Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

“…The SMA is a newly developed metaheuristic algorithm that is inspired by the slime moulds natural oscillation mode. …”
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Hybrid artificial immune system-genetic algorithm optimization based on mathematical test functions by Ali M.O., Koh S.P., Chong K.H., Yap D.F.W.

“…The hybrid includes two processes; firstly, AIS is the attraction among the researchers as the algorithm. This enables it to develop local searching ability and efficiency yet the convergence rate for AIS is preferably not precise compared to the GA. …”

Modified multi verse optimizer for solving optimization problems using benchmark functions by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

“…Firstly, an average position selection mechanism is proposed for solving the local optima problem and secondly, the MVO algorithm is hybrid with another metaheuristics algorithm namely the Sine Cosine Algorithm (SCA) for better balancing the exploration and exploitation of standard MVO algorithm so that it can improve its searching capability. …”
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Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function by Mohamed, Najihah

“…The optimisation technique consists of exact algorithm, and approximate algorithm. The approximate algorithm is a good technique to be highlighted since it is a feasible way to develop an easier, more convenient curve fitting method, that will save great computation, solve a large scale problem and produce a better quality end result. …”
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Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

“…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…Improving localization accuracy and reducing development costs are pivotal keys and main issues in managing and administrating wireless sensor networks (WSNs). …”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

“…Multiple Templates Anomaly Detection (MTAD) strategy is proposed to describe the local anomaly degree through distance functions computed from learning dataset. …”
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Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…This paper serves as a comprehensive background on localization algorithms and methods used in wireless sensor networks, offering insights for researchers to develop efficient localization algorithms tailored to specific application requirements in diverse work environments.…”
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Modified multi-verse optimizer for solving numerical optimization problems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

“…Firstly, an average position selection mechanism is proposed for solving the local optima problem and secondly, the MVO algorithm is hybrid with another metaheuristics algorithm namely the Sine Cosine Algorithm (SCA) for better balancing the exploration and exploitation of standard MVO algorithm so that it can improve its searching capability. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…Many variants have been developed to cope with this problem and improve algorithm performance. …”
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An Evaluation of Machine Learning Algorithms for Missing Values Imputation by Kohbalan, Moorthy, Ali, Mohammed Hasan, Mohd Arfian, Ismail, Chan, Weng Howe, Mohd Saberi, Mohamad, Safaai, Deris

“…The purpose of our review article is to focus on the developments of current techniques. For scientists rather applying different or newly develop algorithms with the identical functional goal. …”
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Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms by Sulaiman, Noorazliza

“…The proposed memetic ABC algorithms have been developed by hybridizing the proposed ABC variants with a local search technique, augmented evolutionary gradient search (EGS). …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Disparity map algorithm for stereo matching process using local based method by Gan, Melvin Yeou Wei

“…Hence, this thesis proposes a local-based SVDM algorithm that increases the accuracy on the complex scenes. …”
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New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

“…To approximate the curvature of the objective function, more available information from the function-values and gradient is employed. …”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness by Noori, Mustafa Sabah, Sahbudin, Ratna K.Z., Sali, Aduwati, Hashim, Fazirulhisyam

“…Therefore, this article introduces a novel Multi-Exemplar Particle Swarm Optimization with Local Awareness (MEPSOLA) as a potent solution. The algorithm presents a developed multi-objective-aware criterion for multi-exemplar selection, adeptly balancing exploration and exploitation to avoid local optima and enhance performance across multiple objectives. …”
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A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

“…Among the latest Evaluation Algorithm (EA) have been developed is Differential Evolution (DE). …”
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