Search Results - (( programming approach evolutionary algorithm ) OR ( java application using algorithm ))
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A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch
Published 2016“…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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Using genetic algorithm for solving N-Queens problem
Published 2023“…Results show that this evolutionary approach is very efficient and able to produce good results compared with other approaches e.g. classical search algorithms or linear programming. � 2010 IEEE.…”
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Solving unit commitment problem with solar photovoltaic and wind energy generation by using multi-agent evolutionary programming technique / Putri Azimah Salleh
Published 2014“…Several Artificial Intelligence (AI) techniques such as Multi Agent and Evolutionary Programming were combine to produce Multi Agent Evolutionary Programming (MAEP) technique. …”
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Dual-head marking performance optimisation via evolutionary solutions
Published 2023“…Also, the performance of the new operators for evolutionary approaches to the time-based problem has been discussed in the paper. � 2005 IEEE.…”
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Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List
Published 2023“…This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority List optimisation technique (MAEP-PL). …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Automated synthesis of mobile game environments and rulesets using a hybridized interactive evolutionary programming approach
Published 2014“…By hybridizing Evolutionary Programming (EP) with Interactive Evolutionary Algorithm (IEA), game rules and its playing environment will be automatically generated for an arcade-type game that can be played on the Android mobile platform. …”
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Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman
Published 2021“…Subsequently, the CI-based sizing algorithm, known as Evolutionary-Dolphin Echolocation Programming Sizing Algorithm (EDEPSA) is formulated to determine the optimal models of each system component such that either Performance Ratio (PR) or Levelized Cost of Electricity (LCOE) of the system is optimized. …”
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Computational intellegence approach for overcurrent relay coordination
Published 2024text::Final Year Project -
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A decomposition/aggregation method for solving electrical power dispatch problems
Published 2023“…A program has been developed to demonstrate the algorithm using the MATLAB programming language. …”
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A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm
Published 2015“…This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. …”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…This research presents an approach to solve the UC problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority Listing optimisation technique (MAEP-PL). …”
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Sudoku Generator based on hybrid algorithm / Faridah Abdul Rahman
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Optimal Integration of Active and Reactive Power DGs in Distribution Network via a Novel Multi-Objective Intelligent Technique
Published 2025“…This work introduces a novel approach called the Multi-Objective Integrated Immune Moth Flame Evolutionary Programming (MO-IIMFEP) algorithm. …”
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