Search Results - (( solution population based algorithm ) OR ( variable optimization based algorithm ))

Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

“…Instead of static aggregate such as a weighted sum, MOGA dynamically determine an aggregate of multiple objective values of a solution based on its relative quality in the current population, typically as the degree to which the solution dominates others in the current population. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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Design of digital circuit structure based on evolutionary algorithm method by Chong, Kok Hen, Aris, Ishak, Bashi, Senan Mahmood, Koh, Johnny Siaw Paw

“…It is largely applied to complex optimization problems. EAs introduce a new idea for automatic design of electronic systems; instead of imagine model, abstractions, and conventional techniques, it uses search algorithm to design a circuit. …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…GA has been employed in resolving many complex combinatorial optimization problems such as CS problems. However, the lack of diversity in a population and the difficulty to locally exploit the solutions within a population creates a setback for GA. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

“…The IWD is a recent metaheuristic population-based algorithm belonging to the swarm intelligent category which simulates the dynamic of the river systems. …”

An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

“…One of the classifications is population vs. trajectory. In this paper, several algorithm techniques based on population and trajectory characteristics are discussed. …”
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Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…To produce a population of initial solution require algorithm that can produce multiple feasible solutions and these solutions must be diverse. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

“…Like other population-based algorithms, WOA generate its population randomly during the exploration and exploitation phases, which could generate values far from the optimum solution or stuck the exploration around local optima. …”
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A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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Iteration strategy and ts effect towards the performance of population based metaheuristics by Nor Azlina, Ab. Aziz, Nor Hidayati, Abdul Aziz, Azlan, Abd Aziz, Tasiransurini, Abdul Rahman, Wan Zakiah, Wan Ismail, Zuwairie, Ibrahim

“…The algorithms can be categorized based on number of agents, either single agent algorithms which are also known as single solution metaheuristics or multi agents algorithms, also known as population-based metaheuristics. …”
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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.

“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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APPROXIMATION ALGORITHM-BASED INITIAL POPULATION GENERATION FOR THE GENETIC ALGORITHM SOLUTION OF THE SET COVERING PROBLEM by MOHAMAD RAZIP, HAJAR

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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems by Sulaiman, Mohd Herwan

“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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