Search Results - (( evolution optimization approach algorithm ) OR ( variable optimization bees algorithm ))

Bees algorithm for Forest transportation planning optimization in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

“…Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. …”
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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.

“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”

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. …”
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Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

“…Two types of extraction machines with unique characteristics to be applied in timber harvest area in Malaysia is combined for timber harvesting with the aim each machine will extract timber suitable to their ability. A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
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Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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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

“…The study concludes that the ABC is more suitable for the multi-variable PD localization task than the GA, PSO, and BA due to its effective balance between local search by onlooker bees and global exploration by scout bees.…”
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A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem by Asaad Shakir, Hameed, Mohd Aboobaider, Burhanuddin, Mutar, Modhi Lafta, Ngo, Hea Choon

“…The primary aim of this study is to propose a hybrid approach which combines Discrete Differential Evolution (DDE) algorithm and Tabu Search (TS) algorithm to enhance solutions of QAP model, to reduce the distances between the locations by finding the best distribution of N facilities to N locations, and to implement hybrid approach based on discrete differential evolution (HDDETS) on many instances of QAP from the benchmark. …”
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Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

“…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

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Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

“…The resource allocation algorithm is developed through three phases, namely Low-Complexity Resource Allocation (LRA), Optimized Resource Allocation (ORA) and Cross-Layer Design of ORA (CLD-ORA). …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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Multiobjective design optimization of a nano-CMOS voltage-controlled oscillator using game theoretic-differential evolution by Ganesan, T., Elamvazuthi, I., Vasant, P.

“…The weighted sum scalarization approach was employed in this work in conjunction with three metaheuristic algorithms: particle swarm optimization (PSO), differential evolution (DE) and the improved DE algorithm (GTDE) (which was enhanced using ideas from evolutionary game theory). …”
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm by Basri Badyalina, Nurkhairany Amyra Mokhtar, Nur Amalina Mat Jan, Muhammad Fadhil Marsani, Mohamad Faizal Ramli, Muhammad Majid, Fatin Farazh Ya'acob

“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica... by Stonier, A.A., Chinnaraj, G., Kannan, R., Mani, G.

“…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. Design/methodology/approach: The optimal modulation index along with the switching angles are calculated for an 11 level inverter. …”
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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization by Chin, Kim On, Teo, Jason Tze Wi

“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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Crosssover-first different evolution: a comprehensive post- Hoc analysis by Jason Teo

“…Explore a new evolutionary optimization approach using Crossover-First Differential Evolution. …”
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