Search Results - (( using evolutionary study algorithm ) OR ( basic optimization based algorithm ))

An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…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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Solving unit commitment problem by using particle swarm optimization technique / Muhammad Aqil Ab Rahman by Ab Rahman, Muhammad Aqil

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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Mobile game application development using evolutionary algorithms by Ong, Jia Hui

“…Evolutionary Programming (EP) is used as the main evolutionary technique in this study. …”
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Evolutionary mating algorithm by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Hamdan, Daniyal, Mirjalili, Seyedali

“…This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. …”
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Evolutionary algorithm approach for solving animal diet formulation by Abd Rahman, Rosshairy, Ramli, Razamin, Jamari, Zainoddin, Ku-Mahamud, Ku Ruhana

“…One of the pillars in animal farming industries is formulation of food for the animal, which is also known as diet formulation.However, the feed component in the aquaculture industry incurs the most expensive operational cost, and has drawn many studies regarding diet formulation.Hence, this study aims to solve animal diet formulation problem with ratio constraint using evolutionary algorithm approach.Actual data with 14 ingredients and 18 nutrients were taken into consideration.The result shows that evolutionary algorithm provides feasible solution in all runs. …”
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

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A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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A Standard Deviation Selection in Evolutionary Algorithm for Grouper Fish Feed Formulation by Soong, Cai Juan, Razamin, Ramli, Rosshairy, Abdul Rahman

“…In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available. Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm. …”
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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…This study focuses on applying and evaluating evolutionary algorithms combined with conventional neural networks to predict building energy consumption in the residential sector. …”

Evaluation of fast evolutionary programming, firefly algorithm and mutate-cuckoo search algorithm in single-objective optimization / Muhammad Zakyizzuddin Rosselan, Shahril Irwan S... by Rosselan, Muhammad Zakyizzuddin, Sulaiman, Shahril Irwan, Othman, Norhalida

“…In this study proposes an evaluation of different computational intelligences, i.e Fast-Evolutionary Algorithm (FEP), Firefly Algorithm (FA) and Mutate-cuckoo Search Algorithm (MCSA) for solving single-objective optimization problem. …”
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Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty by Ehteram, Mohammad, Mousavi, Sayed Farhad, Karami, Hojat, Farzin, Saeed, Singh, Vijay P., Chau, Kwok Wing, El-Shafie, Ahmed

“…Results showed the volume of water to be released for the future period, based on all evolutionary algorithms used, was less than for the base period, and the bat algorithm with high-reliability index and low vulnerability index performed better among other evolutionary algorithms.…”
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A Systematic Exploration of Mutation Space in a Hybridized Interactive Evolutionary Programming for Mobile Game Programming by Jia Hui Ong, Jason Teo

“…Evolutionary programming is the core Evolutionary Algorithm (EA) used in this study where it is hybridized with Interactive Evolutionary Algorithm (IEA) to generate different rulesets that was played on a custom arcade-type mobile game. …”
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A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints by Jia, Hui Ong, Teo, Jason Tze Wi

“…Practically allevolutionary optimization studies have focused exclusively on the use of number of fitness evaluations as the constraining factor when comparing different evolutionary algorithms (EAs). …”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

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Multi-objective optimization of all-wheel drive electric formula vehicle for performance and energy efficiency using evolutionary algorithms by Tey, Jing Yuen, Ramli, Rahizar

“…A new method based on constraint multi-objective optimization using evolutionary algorithms is proposed to optimize the powertrain design of a battery electric formula vehicle with an all-wheel independent motor drive. …”
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A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique by Chuah, How Siang

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