Search Results - (( simulation optimization method algorithm ) OR ( variable objective evolutionary algorithm ))

Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

“…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris by Mohammad Aris, Ahmad Amiruddin

“…The proposed co-simulation process is developed by coupling building energy simulation (BES) software, Energy Plus with multi-objective evolutionary programming (MOEP) algorithm which is implemented in Matlab using coupling software, BCVTB. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

“…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”

A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour, Masoud, Ali, Zaipatimah, Othman, Muhammad Murtadha, Bo, Rui, Javadi, Mohammad Sadegh, Ridha, Hussein Mohammed, Alrifaey, Moath

“…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Synchronizing Artificial Intelligence Models for Operating the Dam and Reservoir System by Allawi, Mohammed Falah, Jaafar, Othman, Ehteram, Mohammad, Mohamad Hamzah, Firdaus, El-Shafie, Ahmed

“…The current study compared the performance of the SML model with popular evolutionary computing methods, namely Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Fuzzy optimization with multi-objective evolutionary algorithms: A case study by P., Vasant, F., Jimenez, G., Sanchez

“…On the other hand, an ad hoc Pareto-based multi-objective evolutionary algorithm to capture multiple non dominated solutions in a single run of the algorithm is described. …”
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A multi-objective evolutionary approach for fuzzy optimization in production planning by P., Vasant, F., Jimenez, G., Sanchez, J.L., Verdegay

“…Results obtained have been compared with the well-known multi-objective evolutionary algorithm NSGA-II. © 2006 IEEE. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Evolutionary and population dynamics of 3 parents differential evolution (3PDE) using self-adaptive tuning methodologies by Teng, Nga Sing, Teo, Jason Tze Wi

“…In this paper, 50 repeated evolutionary runs for each of 20 well-known benchmarks were carried out to test the proposed algorithms against the original 4-parents DE algorithm. …”
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Hybrid genetic algorithms and line search method for industrial production planning with non-linear fitness function by Vasant, Pandian

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Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

“…Subsequently, a new multi-objective optimisation technique named Multi-Objective Hybrid Evolutionary-Barnacles Mating Optimisation (MOHEBMO) was developed to solve the minimization problems involving the total generation cost and total emission of harmful gasses in a multi-objective mode. …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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A Hybrid of Optimization Method for Multi-Objective Constraint Optimization of Biochemical System Production by Mohd Arfian, Ismail, Safaai, Deris, Mohd Saberi, Mohamad, Mohd Adham, Isa, Afnizanfaizal, Abdullah, Muhammad Akmal, Remli, Mohi-Aldeen, Shayma Mustafa

“…The proposed method combines Newton method, Strength Pareto Evolutionary Algorithm (SPEA) and Cooperative Co-evolutionary Algorithm (CCA). …”
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Economic power dispatch solutions incorporating stochastic wind power generators by moth flow optimizer by Alam, Mohammad Khurshed, Mohd Herwan, Sulaiman, Sayem, Md. Shaoran, Khan, Rahat

“…The introduction of renewable energy sources into the smart grid of the present enables the emergence of novel optimization problems with an abundance of new variables. This study's primary purpose is to apply state-of-the-art variations of the differential evolution (DE) algorithm for single-objective optimization and selected evolutionary algorithms for multi-objective optimization issues in power systems. …”
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Route optimization using shortest path method / Muhamad Faisal Amin Shakri by Shakri, Muhamad Faisal Amin

“…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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Asynchronous simulated kalman filter optimization algorithm by Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd Aziz, Tasiransurini, Ab Rahman

“…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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