Search Results - (( developing objective evolutionary algorithm ) OR ( based applications testing algorithm ))

Towards Software Product Lines Optimization Using Evolutionary Algorithms by Jamil, Muhammad Abid, K Nour, Mohamed, Alhindi, Ahmed Hasan, Awang Abu Bakar, Normi Sham, Arif, Muhammad, Muhammad Aljabri, Tareq

“…We report on the problem encoding, variation operators and different types of algorithms: Indicator Based Evolutionary Algorithm (IBEA), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithms based on Decomposition (MOEA/D) and Strength Pareto Evolutionary algorithm II (SPEA-II). …”
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Adaptive glioblastoma detection using evolutionary-based algorithm / Nurul Amira Mohd Ali by Mohd Ali, Nurul Amira

“…Hence, this project was proposed to help in overcome the problems. The objectives of the project are to design and develop a prototype of adaptive Glioblastoma detection using Evolutionary-based algorithm to assist in detecting brain tumor and also to test the prototype’s functionality and detection accuracy. …”
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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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Software testing optimization for large systems using agent-based and NSGA-II algorithms by Jamil, Muhammad Abid, Nour, Mohamed Kidher, Awang Abu Bakar, Normi Sham

“…The performance of a multi-objective Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and evolutionary multi-agent system (EMAS) on Feature Models (FMs) to enhance large System testing is reported in this study.…”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem by Ibrahim Abaker , Targio Hashem

“…The multi-objective approaches which are, Sorting Genetic Algorithm II (NSGA-II) and Strength Pareto Evolutionary Algorithm II (SPEA2) are applied to find the Pareto front of the Makespan and total cost. …”
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

“…Further, a comparison between elitism and non-elitism used has been conducted attributable to no study has been conducted yet in comparing the application of elitism and non-elitism. As a result, this study has thus shown that the multi-objective approach to evolutionary robotics in the form of the elitist PDE-EMO algorithm can be practically used to automatically generate controllers for RF-Iocalization behavior in autonomous mobile robots.…”
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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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Real-time optimal switching angle scheme for a cascaded H-Bridge inverter using Bonobo Optimizer by Abdul Wahab, Noor Izzri, Abdulsalam Taha, Taha, Hassan, Mohd Khair, Zaynal, Hussein I., Taha, Faris Hassan, Mohammed Hashim, Abdulghafor

“…To prove that the BO algorithm works, tests were done on a three-phase, seven-level CHB-MLI that compared it to other evolutionary algorithms like the genetic algorithm (GA) and particle Swarm optimization (PSO). …”
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A hybrid optimization technique for solving economic emission load dispatch problems by Aisyah binti Nordin

Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…The simulation results indicate that the algorithm is able to segregate and assign the tasks for each scanning head and also able to find the shortest scanning path for different types of objects coordination. …”
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A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem by Ong, Kok Meng

“…Both MFPA and CPA were first evaluated using twenty-five well-known benchmark functions with different characteristics and seven Congress on Evolutionary Computation (CEC) 2017 test functions. Their convergence characteristic and computational efficiency were analysed and compared with eight widely used metaheuristic algorithms, with the superiority validated using the Wilcoxon signed-rank test. …”
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

“…The whole constraint analyzer and the fitness function were combined with four SBTs (genetic algorithm, evolutionary algorithm, simulating annealing, and quantum genetic algorithm). …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

“…At this stage, a classical Artificial Neural Network (ANN) is developed using systematic training and testing procedures. …”
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Solving nonlinear system of equations based on MATLAB GUI / Muhammad Azri Azman Shah by Azman Shah, Muhammad Azri

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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.

“…This paper introduces the Multi-objective Optimization Hybrid Evolutionary-Barnacles Mating Optimizer (MOHEBMO) algorithm, developed to solve multiple objectives simultaneously using the weighted sum method. …”

Multi-criteria evolutionary regression test prioritization for dynamic object-oriented programs by Bello, Abdulkarim, Md. Sultan, Abubakar, Shehu, Sirajo

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Multiobjective evolutionary algorithms NSGA-II and NSGA-III for software product lines testing optimization by Jamil, Muhammad Abid, Alhindi, Ahmad, Arif, Muhammad, Nour, Mohamed K, Awang Abu Bakar, Normi Sham, Aljabri, Tareq Fahad

“…This research, reports on the performance of a multi-objective Evolutionary Algorithms Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and NSGA-III on Feature Models (FMs) to optimize SPL testing.…”
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Chaotic mutation immune evolutionary programming for photovoltaic planning in power system / Sharifah Azma Syed Mustaffa by Syed Mustaffa, Sharifah Azma

“…Consequently, the third objective is to develop a new optimization technique termed as Multi-Objective Chaotic Immune Evolutionary Programming (MOCMIEP) for optimal location and sizing of DGPV installations in multi-objective problem to minimize the FVSI value and transmission loss. …”
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Pareto ensembles for evolutionary synthesis of Neurocontrollers in a 2D maze-based video game by Tse, Guan Tan, Jason Teo, Chin, Kim On, Patricia Anthony

“…A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
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