Search Results - (( solution construction method algorithm ) OR ( based optimization based algorithm ))
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…(iii) It is a constructive-based meta-heuristic algorithm which means, the solution is incrementally constructed (step by step) until the complete solution is obtained (Noferesti and Shah-Hosseini, 2012). …”
thesis::doctoral thesis -
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…Such a finding indicates that the exploitation of bio-inspired algorithms with ideal combination of wrapper/filtered method can contribute in finding the optimal features to be used in data mining model construction.…”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty
Published 2024“…The RUL prediction uncertainty with a 95% confidence interval (CI) is also analyzed. The GSA algorithm optimizes the hyperparameters of the LSTM network to construct an optimal model. …”
Conference Paper -
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…A MySQL database was created to analyze the optimization results and speed up computations of the optimization algorithm. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…First and foremost, this study examines the proposed crossover and mutation operators on the problems of slow convergence and premature convergence to suboptimal solution. Second of all, this study operates within experimental design with Taguchi method to discover the optimal design factors for the two proposed genetic operators. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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Optimization of Digital Electronic Circuit Structure Design Using Genetic Algorithm
Published 2008“…The results show that the proposed method is able to produce the optimized circuit with lesser number of gates compared to the conventional methods. …”
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Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques
Published 2014“…The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. …”
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An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm
Published 2025“…Risk-based portfolio optimization has become increasingly crucial due to the limitations and underperformance of traditional Mean-Variance (MV) portfolios. …”
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Multi-objective and multi-criteria decision making for Technoeconomic optimum design of hybrid standalone renewable energy system
Published 2025“…In this paper, the multi-objective Dragon fly algorithm is developed based on mutation scheme and crossover tactic algorithm is advanced to handle a lack of diversity and poor convergence, while non-dominated sorting and crowding distance strategy is addressed to store the best found optimum solutions in the achieve. …”
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Multi-objective and multi-criteria decision making for Technoeconomic optimum design of hybrid standalone renewable energy system
Published 2024“…In this paper, the multi-objective Dragon fly algorithm is developed based on mutation scheme and crossover tactic algorithm is advanced to handle a lack of diversity and poor convergence, while non-dominated sorting and crowding distance strategy is addressed to store the best found optimum solutions in the achieve. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. This study constructs the flow of DNN based method with the K-Means algorithm. …”
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Development of an integrated scheduling model for handling equipment in automated port container terminals
Published 2014“…In addition, results proved that the modified meta-heuristic algorithm is able to find near optimal solutions and on average, the solutions found by the GA algorithm are only 0.2% worse than the optimal solutions and in the worst case in the test cases this difference is 2.3% which is acceptable. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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