Search Results - (( using optimization model algorithm ) OR ( using optimization problem algorithm ))
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences
Published 2018“…Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. …”
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Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization
Published 2018“…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
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Research Report -
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference
Published 2018“…Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. …”
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Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm
Published 2021“…Specific optimization model and algorithm were developed to solve the problem. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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Optimization of multi-holes drilling path using particle swarm optimization
Published 2018“…The problem is modeled as traveling salesman problem (TSP) and optimized using Particle Swarm Optimization (PSO). …”
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Book Chapter -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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Optimization of multi-holes drilling toolpath using tiki-taka algorithm
Published 2024“…The study aims to model the MDMT toolpath using the Traveling Salesman Problem (TSP) concept, apply TTA to optimize this model, and validate the model and algorithm through machining experiments on this problem. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Furthermore, the original DA is only suitable for solving continuous optimization problems. Although there is a binary version of the algorithm, it cannot be directly used for solving discrete optimization problems like the Traveling Salesman Problem (TSP). …”
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Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm
Published 2023“…This is a clear indication that the developed TTA algorithm is reliable and could be used in optimizing a real-life problem by the resequence of the assembly task, thus reducing the cycle time and could reduce the total energy consumption by machinery…”
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Multi-state PSO GSA for solving discrete combinatorial optimization problems
Published 2016“…These four algorithms can be used to solve discrete combinatorial optimization problems (COPs). …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Assessment of metaheuristic algorithms to optimize of mixed-model assembly line balancing problem with resource constraints
Published 2020“…In this study, an assessment of metaheuristic algorithms to optimize MMALBP was conductedby using four popular metaheuristics , namely particle swarm optimization (PSO), simulated annealing (SA), ant colony optimization (ACO),and genetic algorithm (GA). …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification
Published 2024“…Secondly, an improved CatBoost algorithm (EBGWO-CatBoost) was proposed, which was a combination of improved GWO algorithm (EBGWO) and CatBoost algorithm, and the optimized GWO algorithm was used to offset the defects of CatBoost algorithm in parameter tuning. …”
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Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh
Published 2018“…At the end, the proposed MOSFP has been used to solve a real-life problem such as optimizing a set of Quality of Services (QoS) objective functions (network models) in WSN. …”
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