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Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization by Ismail N.L., Musirin I., Dahlan N.Y., Mansor M.H., Senthil Kumar A.V.

“…MOHEBMO combines Evolutionary Programming and Barnacles Mating Optimizer to find the best trade-off among conflicting objectives. …”

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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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

“…This schema takes into account uncertainty and makes a trade-off among conflicting multi-objectives at the same time. …”
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Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables by ALAhmad A.K., Verayiah R., Ramasamy A., Marsadek M., Shareef H.

Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

“…The efficiency of the algorithm was compared to a multi-objective genetic algorithm (MOGA) as well. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Multi depot dynamic vehicle routing problem with stochastic road capacity for emergency medical supply delivery in humanitarian logistics by Anuar, Wadi Khalid

“…The model proposed is based on Markov Decision Processes (MDP) modelling framework as part of reinforcement learning (RL) solution approach. Through this model, multi objectives, multi depot, multi trip and split delivery among homogeneous fleet of vehicle are addressed. …”
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Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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Computational intelligence based power system security assessment and improvement under multi-contingencies conditions / Nor Rul Hasma Abdullah by Abdullah, Nor Rul Hasma

“…The contributions of the studies among the others are the development EP and AIS engine for CPP considered multi-contingencies (N-m), the development of EP and AIS engine for FACTS installation considered multi-contingencies (N-m) for the determination of FACTS placement using SVSI and optimal sizing of FACTS using EP and AIS, the development of new technique for OGS based on EP optimization technique and the development of multi-objective EP and AIS engines for CRPC considered multi-contingencies (N-m)…”
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Study on the microbial growth inhibition by using pineapple leaves juice by Amirah, Ya'acob

“…The contributions of the studies among the others are the development EP and AIS engine for CPP considered multi-contingencies (N-111). …”
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Computational intelligence based power system security assessment and improvement under multicontigencies conditions by Nor Rul Hasma, Abdullah

“…The minimizations of SVSJ and transmission loss are used as two separate objective functions for the development of optimization technique.The effect of reactive power load variation.on transmission loss in the system is also investigated.Consequently,the EP optimization technique is extended for the evaluation of the operating generator scheduling (OGS) to be applied on reactive power control in power system.The results obtained from the study can be used by the power system operators to make a decision either to achieve minimal SVSJ, minimal transmission loss or minimal installation cost.This has also avoided all generators to dispatch power at the same time.Finally,a novel multi-objective Constrained Reactive Power Control (CRPC) algorithm using the state-of-the-art of EP for voltage stability improvement has been developed.A performance comparison with Artificial Immune System (AIS) in terms of SVSJ and loss minimization was made and it is found that the proposed algorithm has been able to produce better results as compared to AIS.The contributions of the studies among the others are the development EP and AIS engine for CPP considered multi-contingencies (N-ni),the development of EP and AIS engine for FACTS installation considered multi-contingencies(N-m) for the determination of FACTS placement using SVSI and optimal sizing of FACTS using EP and AIS, the development of new technique for OGS based on EP optimization technique and the development of multi-objective EP and AIS engines for CRPC considered multi-contingencies (N-m).…”
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Logistics center location-inventory-routing problem optimization: a systematic review using PRISMA method by Liu, Lihua, Lee, Lai Soon, Seow, Hsin Vonn, Chen, Chuei Yee

“…First, the most popular problems among researchers are the multi-period multi-product problem, the multi-echelon single-link problem, and the multi-depot multi-retailer problem. …”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

“…GA is widely known as a multi-purpose searching procedure commonly use in optimization and approximation field. …”
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Load margin expansion for sustainable power system operation by E.E, Hassan, T.K.A, Rahman, Nazrulazhar, Bahaman, Zuhaina, Zakaria

“…From the results it shows that the multi objective ATBFO optimization is able to give better overall improvement among all objective functions of SCRPP.…”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

“…The described model was resolved by linear programming and evolutionary algorithms in Microsoft Excel (Solver). …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem by Sulaiman M.A.H.B., Suliman A., Ahmad A.R.

Image Improvement Technique Using Feed Forward Neural Network by Abu Saeeda, Omar Abdulmola

“…This research is aimed to develop an efficient image enhancement technique using multi layer Feedforward neural network. A nonlinear digital filter has been introduced as a promising solution for improving the image quality.The filter, which is named unsharp mask filter based neural network,significantly enhances the sharpness of image while highlights its details(edges and lines).In this thesis sharpening of image details has been obtained.Multi-layer Feed forward neural network with back propagation algorithm known as Multilayer Perceptron (MLP) is used to control the level of contrast enhancement.Grayscale blurred images were also used in this study.The results have been evaluated using mean square error as well as grayscale histogram distribution for sharpening of image details.Comparison among 3x3, 5x5 and 7x7 mask sizes has shown that least mean square error has been achieved by using the 3x3 mask size. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Optimization of reservoir operation at Klang Gate Dam utilizing a whale optimization algorithm and a L�vy flight and distribution enhancement technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., El-Shafie A.

“…LFWOA had attained the least shortage. The LFWOA algorithm was the most robust among the MHAs (1.88). …”

A multi-layer perceptron approach for customer churn prediction by Mokhairi, Makhtar, Mohd Khalid, Awang, Mohd Nordin, Abdul Rahman

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