Search Results - (( using optimization method algorithm ) OR ( problem implementation level algorithm ))
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Combined heat and power (CHP) economic dispatch solved using Lagrangian relaxation with surrogate subgradient multiplier updates
Published 2023“…Flexibility for the choice of algorithm is given at the lower levels optimization techniques with the condition that the algorithm is able to improve its search at each iteration. …”
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Harmony search-based robust optimal controller with prior defined structure
Published 2013“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi...
Published 2024“…This study focuses on "Comparative Analysis of Line Search Methods in SD Algorithm for Unconstrained Optimization Problems". …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. …”
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6
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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7
Development of committee machine models for multiple response optimization problems
Published 2014“…Four methodologies are to make four different CM models to solve MRO problems. The fifth methodology proposes the final algorithm which uses four CM models together to solve MRO problems. …”
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8
A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation
Published 2019“…First, three different optimization algorithms, namely particle swarm optimization, differential evolution, and whale optimization algorithm, have been applied. …”
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Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
Published 2018“…Heuristic optimization algorithms are broadly used to solve many engineering problems. …”
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Dynamic Economic Dispatch For Power System
Published 2016“…This research finds large variable size DED problems can be easily implemented, PSO method is reliable and is suitable for real-time analysis. …”
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12
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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13
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…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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Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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15
Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…After that, a bi-objectives algorithm is tested for comparing purposes and this contributed for the next two sub-objectives that is 3) to test the feasibility for implementing the PDE hybrid FFNN. 4) to compare single objective and multi-objective optimization algorithms performances. …”
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A multi-objective routing mechanism for energy management optimization in SDN multi-control architecture
Published 2022“…This paper proposed and implemented an energy-aware routing multi-level and mapping problem (EARMLP) algorithm to minimize the overall power consumption in Software-Defined Networking (SDN)-based core networks. …”
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Harris Hawk Optimization-Based Deep Neural Networks Architecture for Optimal Bidding in the Electricity Market
Published 2022“…The state-of-the-art frameworks used for simulating strategic bidding decisions in deregulated electricity markets (EM’s) in this article are bi-level optimization and neural networks. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management
Published 2009“…After formulating the stochastic model using Mean Absolute Deviation, the problem is then investigated using the Pareto front solution of efficient frontier of the resulting multiobjective optimization problem by using the Weighted Sum Method as well as the ε-constraint method in order to obtain the Pareto Optimal Curve which generates a wide selection of optimization solutions for our problem. …”
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management
Published 2009“…After formulating the stochastic model using Mean Absolute Deviation, the problem is then investigated using the Pareto front solution of efficient frontier of the resulting multiobjective optimization problem by using the Weighted SumMethod as well as the e-constraint method in order to obtain the Pareto Optimal Curve which generates a wide selection of optimization solutions for our problem. …”
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Final Year Project
