Search Results - (( variable optimization based algorithm ) OR ( loading optimization approach algorithm ))

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”

Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

“…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”

Optimizing energy and reserve minimization in a sustainable microgrid with electric vehicle integration: dynamic and adjustable manta ray foraging algorithm by Abed, Adnan Ajam, Suwaed, Mahmood Sh., Al-Rubaye, Ameer H., Awad, Omar I., Mohammed, M.N, Hai, Tao, Kadirgama, Kumaran, Karah Bash, Ali A. H.

“…This paper presents a novel approach for optimizing energy and reserve minimization in a sustainable integrated microgrid with electric vehicles (EVs) by the use of the dynamic and adjustable Manta Ray Foraging (DAMRF) algorithm. …”
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Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability by Ahmad, S., Albatsh, F.M., Mekhilef, Saad, Mokhlis, Hazlie

“…Furthermore, to verify the suitability of the explored locations, a comparative study has been conducted after placing UPFC in the present locations and other locations obtained using optimization techniques like particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA), and bacteria foraging algorithm (BFA). …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

“…The backward reduction method (BRM) is then applied to streamline the number of generated scenarios, reducing computational efforts. To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”

A practical multi-objective design approach for optimum exhaust heat recovery from hybrid stand-alone PV-diesel power systems by Yousefi M., Kim J.H., Hooshyar D., Yousefi M., Sahari K.S.M., Ahmad R.B.

Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement by Hannan M.A., Ali J.A., Hossain Lipu M.S., Mohamed A., Ker P.J., Indra Mahlia T.M., Mansor M., Hussain A., Muttaqi K.M., Dong Z.Y.

Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty by Asih, Hayati Mukti

“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

“…This algorithm looks for a short path from the subscriber station (SS) node to BS, while the optimal path is achieved when the whole path has the lowest EbMR. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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Vehicle Routing Problem with Simultaneous Pickup and Delivery by Sze, San Nah, Sek, Siaw Ying Doreen, Sze, Jeeu Fong, Cheah, Wai Shiang, Chiew, Kang Leng

“…The considerable data size has increased the difficulty for it to be solved by using mathematical programming or combinatorial optimization. A heuristic approach based on the Variable Neighborhood Search (VNS) is proposed. …”
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A high-performance control scheme for photovoltaic pumping system under sudden irradiance and load changes by Talbi, Billel, Krim, Fateh, Rekioua, Toufik, Mekhilef, Saad, Laib, Abdelbaset, Belaout, Abdesslam

“…The proposed algorithm is based on a current control approach of the boost converter with a model predictive current controller to select the optimal control action. …”
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A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Mohd Shawal, Jadin

“…This study will use Teaching Learning-Based Optimization (TLBO) as the main optimizer for the problem simulation. …”
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Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

“…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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A practical multi-objective design approach for optimum exhaust heat recovery from hybrid stand-alone PV-diesel power systems by Yousefi, M., Kim, J.H., Hooshyar, D., Yousefi, M., Sahari, K.S.M., Ahmad, R.

“…In this paper, a new approach for practical design of these systems based on varying engine loads is presented. …”
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Control of polystyrene batch reactors using neural network based model predictive control (NNMPC): an experimental investigation by Hosen, M.A., Hussain, Mohd Azlan, Mjalli, F.S.

“…The reactor is then run to track the optimized temperature set-point profile. In this work, a neural network-model predictive control (NN-MPC) algorithm was implemented to control the temperature of a polystyrene (PS) batch reactors and the controller set-point tracking and load rejection performance was investigated. …”
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Online auto-tuned proportional-integral controller using particle swarm optimization for dual active bridge DC-DC converter by Suliana, Ab Ghani

“…APSO-PI is an auto-tuned PI using the PSO algorithm where the optimal values of Kp and Kiwere tuned at the initial control process only. …”
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Review on computational strategies for bi-layered metal powder compaction by Mohd Tahir, Suraya, Mohd Yusoff, Syamimi, Mohamed Ariff, Azmah Hanim, Supeni, Eris Elliandy, Anuar, Mohd Shamsul

“…A scrutinize part is the implementation of algorithm to describe powder behavior under double loading as well as to relate with other mechanical variables that eventually require expertise on computational plasticity knowledges involving horizontal contacts. …”
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