Search Results - optimal ((flow algorithm) OR (((((bat algorithm) OR (_ algorithm))) OR (bees algorithm))))

Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
Get full text
Get full text

BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

“…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
Get full text
Get full text

Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

“…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
Get full text
Get full text
Get full text

HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION by Kappagantula, S., Vojjala, S., Iyer, A.A., Velidi, G., Emani, S., Vandrangi, S.K.

“…Swarm Intelligence is inspired by naturally occurring swarm systems suchas Ant Colony, Bees Hive, or Bats. The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
Get full text
Get full text

Artificial bee colony algorithm for solving optimal power flow problem by Le Dinh, L., Vo Ngoc, D., Vasant, P.

“…This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. …”
Get full text
Get full text

Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
Get full text
Get full text
Get full text

Comfort and energy consumption optimization in smart homes using bat algorithm with inertia weight by Mohamad Razwan, Abdul Malek, Nor Azlina, Ab. Aziz, Alelyani, Salem, Mohana, Mohamed, Farah Nur Arina, Baharudin, Zuwairie, Ibrahim

“…Moreover, the comfort level achieved by BA with exponential inertia weight is found to be better than previously reported works using firefly algorithm, genetic algorithm, ant colony optimization, and artificial bee colony algorithm. …”
Get full text
Get full text
Get full text
Get full text

Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm by Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim

“…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
Get full text
Get full text
Get full text

Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

“…In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
Get full text
Get full text

Minimizing power loss using modified artificial bee colony algorithm / Nur Azlin Ashiqin Mohd Amin ...[et al.] by Mohd Amin, Nur Azlin Ashiqin, Jamaluddin, Siti Hafawati, Muhammat Pazil, Nur Syuhada, Mahmud, Norwaziah, Kimpol, Norhanisa

“…In this paper, the Modified Artificial Bee Colony (MABC) algorithm is implemented to solve the power system's optimal reactive power flow problem. …”
Get full text
Get full text
Get full text

A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

“…Metaheuristic algorithms have received much attention recently for solving different optimization and engineering problems. …”
Get full text
Get full text
Get full text
Get full text

Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin by Mohd Zin, Nurul Syakira

“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
Get full text
Get full text

Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
Get full text
Get full text
Get full text

Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin by Mohd Zin, Nurul Syakira

“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
Get full text
Get full text

Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia by Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.

“…Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. …”

Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm by Chong K.L., Lai S.H., Ahmed A.N., Wan Jaafar W.Z., El-Shafie A.

“…Ant colony optimization; Hydroelectric power; Hydroelectric power plants; Investments; Particle swarm optimization (PSO); Reservoirs (water); Stream flow; Water supply; Ant colony algorithms; Hydro-power generation; Hydropower reservoirs; Optimization algorithms; Particle swarm optimization algorithm; Reservoir performance; Streamflow generations; Uncertainty and variability; Genetic algorithms…”

Acoustic emission partial discharge localization in oil based on artificial bee colony by Lim, Zhi Yang, Azis, Norhafiz, Mohd Hashim, Ahmad Hafiz, Mohd Radzi, Mohd Amran, Norsahperi, Nor Mohd Haziq, Mohd Ariffin, Azrul

“…Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
Get full text
Get full text
Get full text

Optimal power flow solutions for power system operations using moth-flame optimization algorithm by Alabd, Salman, Mohd Herwan, Sulaiman, Muhammad Ikram, Mohd Rashid

“…The comparison proves that MFO gives better results compared to the other compared algorithms. MFO gives a reduction of 14.50% compared to 13.38 and 14.15% for artificial bee colony (ABC) and Improved Grey Wolf Optimizer (IGWO) respectively…”
Get full text
Get full text
Get full text
Get full text

Frequency stabilization in interconnected power system using bat and harmony search algorithm with coordinated controllers by K., Peddakapu, M. R., Mohamed, P., Srinivasarao, P.K, Leung

“…To enhance the outcome of the proposed 2DOF–TIDN controller, its gain parameters are optimized with the use of a newly designed hybrid bat algorithm-harmony search algorithm (hybrid BA–HSA) technique. …”
Get full text
Get full text
Get full text
Get full text

Estimation of optimal machining control parameters using artificial bee colony by Norfadzlan, Yusup, Arezoo, Sarkheyli, Azlan, Mohd Zain, Siti Zaiton, Mohd Hashim, Norafida, Ithnin

“…Five machining control parameters that are optimized using ABC algorithm include traverse speed (V), waterjet pressure (P), standoff distance (h), abrasive grit size (d) and abrasive flow rate (m). …”
Get full text
Get full text
Get full text