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Improvement DACS3 Searching Performance using Local Search by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

“…Embedding such behavior has improved quality of solution and time taken to reach the solution. However, the algorithm performance is reduced for large data set. …”
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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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Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

“…These binary variables are used to locally search for optimum solution. SDAA is developed using the concept of male ants performing nuptial flights to generate new superior colonies. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

“…This development then introduces the Se-PSO algorithm in which the particles are segmented to find a local optimal solution at the beginning and later sought by the PSO algorithm. …”
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Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis by Ashraf Osman, Ibrahim, Siti Mariyam, Shamsuddin, Abdulrazak, Yahya Saleh, Ahmed, Ali, Mohd Arfian, Ismail, Shahreen, Kasim

“…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

“…Generally, every step of the data processing sequence affects the accuracy of EEG source localization. In this paper, we introduce a fused multivariate empirical mode decomposing (MEMD) and inverse solution algorithm with an embedded unsupervised eye blink remover in order to localize the epileptogenic zone accurately. …”
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Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

“…Generally, every step of the data processing sequence affects the accuracy of EEG source localization. In this paper, we introduce a fused multivariate empirical mode decomposing (MEMD) and inverse solution algorithm with an embedded unsupervised eye blink remover in order to localize the epileptogenic zone accurately. …”
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Improved elitist genetic algorithm for reactive power planning in power system / Mohamad Fadhil Mohd Kamal by Mohd Kamal, Mohamad Fadhil

“…This thesis presents a newly developed technique for the improvement of the elitist binary genetic algorithms (EGA) in implementing the reactive power planning (RPP) in power system. …”
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Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem by Nurdiyana, Jamil

“…Firstly, the modified SCA (MSCA) model with cost-based local search strategy is developed. Then, the MSCA is hybridized with TS to prohibit revisiting the previous solutions. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

“…This study developed an optimized variation of the DV-Hop localization algorithm for anisotropic wireless sensor networks. …”
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A hybrid algorithm of source localization based on hyperbolic technique in WSN by Kabir, H., Kanesan, J., Reza, A.W., Ramiah, H.

“…Firstly ML is applied in the position and velocity localization data. Additionally, GA is implemented to acquire the globally best solution of localization parameters from non-linear equations set of ML solution. …”
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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

“…Most practical discrete and mixed discrete optimization problems are nonlinear and known to have more than one locally optimal solution. This suggests the need for global optimization techniques which seek the best solution amongst multiple local optima. …”
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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

“…In IWDSA, SA is integrated to enhance solution quality and prevent IWD from getting trapped in local minima. …”
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The concept of wound healing algorithm by Jonathan Likoh Juis @ Juise, Teong, Khan Vun, Ryan MacDonnell Andrias, Jetol Bolongkikit, Siti Hasnah Tanalol, Asni Tahir

“…Since optimisation problems have many local optimal solutions and non-linear patterns, there will be no global solution, reoptimisation could be a solution. …”
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An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints by Noraini, Mohd Razali

“…Therefore, metaheuristic method based genetic algorithm has been developed to obtain feasible and optimal solution with less computation time. …”
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Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

“…The main problem with this clustering method is its tendency to converge to local optima. The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Local search heuristics for elective surgery scheduling considering patient urgency by Rashid, N. S. A., Rahmin, N. A. A., Leong, W. J., Mohamed Ali, Nazihah

“…As the model consume a high computational time to solve for a large-scale instance, we developed a local search algorithm based on a simple heuristic to deal with the problem. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

Embedding Malaysian House Red Ant Behavior into an Ant Colony System by Ali Othman, Zulaiha, Md Rais, Helmi, Hamdan, Abdul Razak

“…Problem statement: Ant Colony System (ACS) is the most popular algorithm used to find a shortest path solution in Traveling Salesman Problem (TSP). …”
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Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

“…Genetic Algorithms (GAs) are stochastic searching algorithms that make the searching process jumps randomly from point to point, thus allowing escape from the local optimum, and search for many sub-optimum points in parallel.This paper presents an evolutionary computation algorithm for enhancing voltage stability. …”
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