Search Results - ((evolution OR (evolution OR evolutionary)) OR solution) programming technique

Minimization of power loss by evolutionary programming using Thyristor Controlled Series Compensators (TCSC) / Fazleza Abdul Latiff by Abdul Latiff, Fazleza

“…This approach is done by using Evolutionary Programming (EP) technique. EP search for the optimal solution by evolving a population of candidate solutions, over a number of generations or iterations. …”
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Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim by Md Daim, Mohd Khairil Izwan

“…This project presents a new technique for solving the optimal power flow problem, in a power system using an Evolutionary Programming and Immune Evolution Programming optimization technique. …”
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Economic power dispatch solution with non-smooth cost functions using differential evolution: article / Muhammad Firdaus Abd Rahim by Abd Rahim, Muhammad Firdaus

“…This thesis proposes a solution for Economic Dispatch problems with non-smooth cost functions using Differential Evolution (DE) algorithm. …”
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Economic power dispatch solution with non-smooth cost functions using differential evolution / Muhammad Firdaus Abd Rahim by Abd Rahim, Muhammad Firdaus

“…This thesis proposes a solution for Economic Dispatch problems with non-smooth cost functions using Differential Evolution (DE) algorithm. …”
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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai, V., Ahmed, Ali Najah, Malek, Marlinda Abdul, El-Shafie, Ahmed, El-Shafie, Amr

“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”
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A hybrid optimization technique for solving economic emission load dispatch problems by Aisyah binti Nordin

Evolutionary cost cognizant regression test prioritization for object-oriented programs based on fault dependency by Bello, AbdulKarim, Md Sultan, Abu Bakar, Abdul Ghani, Abdul Azim, Zulzalil, Hazura

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Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system by Faris A., Musirin I., Jelani S., Ismail S.A., Mansor M.H., Senthil Kumar A.V.

“…A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). …”

Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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Computational intelligence based approach for enhanced distance relay design by Anis Nabilah Mohd Sarwani

Multi-DGPV Planning Using Artificial Intelligence by Abdullah A., Musirin I., Othman M.M., Rahim S.R.A., Sentilkumar A.V.

“…The Integrated Immune Moth Flame Evolution Programming (IIMFEP), a unique hybrid optimization technique, was utilized to identify the ideal DGPV size and location for base case conditions and under load variations. …”

Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai V., Ahmed A.N., Malek M.A., El-Shafie A., El-Shafie A.

“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”

Solving unit commitment problem with wind energy using artificial immune evolutionary programming optimization technique / Mohamad Fitri Ramli by Ramli, Mohamad Fitri

“…The result are shown to verify the performance of Artificial Immune Evolutionary Programming technique.…”
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Solving unit commitment with wind power using artificial immune evolutionary programming optimization technique: article / Mohamad Fitri Ramli by Ramli, Mohamad Fitri

“…This paper propose a solution to unit commitment problem with wind power using artificial immune evolutionary programming The objective of this paper is to find the suitable generation scheduling which can minimize the operation cost with subjmted to various constrain The main idea of this paper is to integrate the use of Artificial fmmune Evolutionary Programming as optimization technique towards Unit Commitment Other than that, this paper also aiming to ieview the effect of addition wind power to the Unit Commitment problem solution. …”
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Evolutionary symbiotic organisms search technique in power scheduling for loss control in power transmission system by Farid N.M.M., Musirin I., Hannon N.H.S., Amroune M., Othman Z., Othman M.M., Shaaya S.A., Zamani M.K.M., Aminuddin N.

“…Symbiotic Organisms Search (SOS) integrated with Evolutionary Programming (EP) is proposed for solving power scheduling problem in the attempt to control the loss values in electric power system. …”

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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Customer profiling-based optimal load shaving solution using Evolutionary Programming technique: article by Zainudin, Muhd Ezzad Zaqwan

“…This paper presents optimal load clipping and shifting using Evolutionary Programming (EP) technique. The problem formulation is based on the basic load clipping and load shifting knowledge. …”
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Modification of species-based differential evolution for multimodal optimization by Al Idrus, Said Iskandar, Syahputra, Hermawan, Firdaus, Muliawan

“…Optimization problem is the problem of maximizing or minimizing a function of one variable or many variables, which include unimodal and multimodal functions. Differential Evolution (DE), is a random search technique using vectors as an alternative solution in the search for the optimum. …”
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Effect of multi-unit and multi-type DG installation using integrated optimization technique in distribution power system planning by Abdullah A., Musirin I., Othman M.M., Rahim S.R.A., Mansor M.H., Shaaya S.A., Aminuddin N., Goel L.K.

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Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List by Othman M.N.C., Rahman T.K.A., Mokhlis H., Aman M.M.

“…The search process is refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. The developed technique is tested on ten generating units test system for a 24-h scheduling period, and the results are compared with the standard Evolutionary Programming (EP), Evolutionary Programming with Priority Listing (EP-PL) and Multi-agent Evolutionary Programming (MAEP) optimisation techniques. …”