Search Results - (( solution construction method algorithm ) OR ( loading optimization based algorithm ))
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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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Multi-objective and multi-criteria decision making for Technoeconomic optimum design of hybrid standalone renewable energy system
Published 2025“…The optimum Pareto front solutions are ranked based on hybrid multi-criteria decision-making method for determining the most favorable solution for the WT/PV/BS system. …”
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Multi-objective and multi-criteria decision making for Technoeconomic optimum design of hybrid standalone renewable energy system
Published 2024“…The optimum Pareto front solutions are ranked based on hybrid multi-criteria decision-making method for determining the most favorable solution for the WT/PV/BS system. …”
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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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Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption
Published 2013“…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The algorithm aids in identifying ideal proportional, integral, and derivative gains based on varying load conditions. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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Student Project -
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An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan
Published 2020“…This project works on developing an efficient network load balancing mechanism based on the Ant Colony Optimization (ACO) algorithm. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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Optimized Load Balancing based Task Scheduling in Cloud Environment
Published 2014“…In this paper, task scheduling strategy based on load balancing Quantum Particles Swarm algorithm (BLQPSO) was proposed. …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Evolutionary Programming (EP) based technique for secure point identification with load shedding technique in power transmission / Abdul Rahman Minhat
Published 2008“…The ability of EP to search for the optimal values of multi-load increase as compared to AVSA which is only able to conduct uniform load increase at several load buses has been identified as the strength of EP over AVSA.…”
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Optimization of load frequency control permancein two-area power system with PID controller using ICA and GSA algorithms / Mumuney Nurullahi Lekan
Published 2018“…The change in the system is signified by the change in the system frequency and tie-line (T-L) load. The performance of LFC has to be tuned properly so that the response can be optimized with a selected controller and algorithm for optimization. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…In addition, for this purpose matrix-based bacteria foraging optimization algorithm traced constraints handling (MBATCH) is developed. …”
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A binary archimedes optimization algorithm and weighted sum method for UFLS in islanded distribution systems considering the stability index and load priority
Published 2023“…This study proposes an under-frequency load-shedding (UFLS) scheme based on a binary Archimedes Optimization Algorithm (BAOA) and the Weighted Sum Method (WSM) to maintain the stability of an islanded distribution system. …”
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Priority-based vehicle-to-grid scheduling for minimization of power grid load variance
Published 2023“…This thesis presents an optimal priority-based Vehicleto-Grid scheduling with the objective to minimize the grid load variance. …”
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