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Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
Published 2016“…An optimal charging strategy for plug-in hybrid electric vehicle (PHEV) is proposed and developed by using evolutionary algorithm to obtain the most suitable charging condition for each PHEV charging. …”
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Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis
Published 2019“…First, we enhance the famous multiobjective evolutionary algorithms, which is a non-dominated sorting genetic algorithm (NSGA-II). …”
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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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Maximax & Maximin and 2FBlockwise Operators: Enhancement in the Evolutionary Algorithm for a Nurse Scheduling Problem
Published 2017“…In doing so, an improved selection operator and crossover operator in an Evolutionary Algorithm (EA) strategy for an NSP is developed as an enhanced algorithm. …”
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Global optimal analysis of variant genetic operations in solar tracking
Published 2023“…Genetic Algorithms (GAs), Evolution Strategies (ES), Evolutionary Programming (EP) and Genetic Programming (GP) are some of the best known types of Evolutionary Algorithm (EA)where it is a class of global search algorithms inspired by natural evolution. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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Optimized processing of satellite signal via evolutionary search algorithm
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Evolutionary Grammars Based Design Framework For Product Innovation
Published 2012“…A new genetic representation of shape grammars is developed in an evolutionary computing environment. …”
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Pareto ensembles for evolutionary synthesis of Neurocontrollers in a 2D maze-based video game
Published 2013“…A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
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Pareto Ensembles for evolutionary Synthesis of Neurocontrollers in a 2D Maze-based video game
Published 2013“…A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
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Multi -Objective Economic Dispatch Using Evolutionary Programming
Published 2023“…This study focused on solving multi-objectives economic dispatch using Heuristic Optimization (HO) technique which is Multi-Objective Evolutionary Programming (MOEP). Increasing amount of total cost and total losses power system forcing developer to seek a plan to reduce the values. …”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…An improved version of Differential Evolution (DE) namely Backtracking Search Algorithm (BSA) is applied to several fed batch fermentation problems and its performance is compared with recent emerging metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and DE. …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…The bacteria foraging optimization (BFO) algorithm is a modern evolutionary computation technique derived from the social foraging behavior of Escherichia coli bacteria. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. HOGA (Hybrid Optimization by Genetic Algorithms) is developed by Dr.Lopez from Zaragoza university in Spain. …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…A multi-objective PACS algorithm based on sequential strategy which considers unit commitment and GMS problem separately is proposed to obtain solution for a proposed GMS model. …”
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