Search Results - (( solution populations using algorithm ) OR ( java application using algorithm ))

Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

“…Algorithms are used to find the solutions through the computer program. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

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Multi-population Genetic Algorithm for Rich Vehicle Routing Problems by Agany Manyiel, Joseph Mabor

“…In this pa�per we present Multi-population Genetic Algorithm for Rich Vehicle Routing Prob�lems (MPGA-RVRP) to provide diversity and delay premature convergence in GA by making use of multiple populations that share potential solutions among each other and evolve independently optimising only one objective. …”
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Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…To produce a population of initial solution require algorithm that can produce multiple feasible solutions and these solutions must be diverse. …”
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The impact of population size on knowledge acquisition in genetic algorithms paradigm: Finding solutions in the game of Sudoku by Abu Bakar, Nordin, Mahadzir, Muhammad Fadhil

“…Population size is an important component in genetic algorithms (GAs).The concept of population in GAs has contributed to a unique searching strategy which empower its search process through the massive volume of the data in a population.The purpose of this study is to see how the impact of population size on genetic algorithms in producing correct solution for a Sudoku puzzle.Sudoku is a Japanese number puzzle game that has become a worldwide phenomenon.The puzzle involves completing a grid of cells by assigning a single number to each cell.The numbers in a row or a column must consist of any one of the numbers from 1 to 9; no repetition is allowed.GA will be used to generate the correct solution of Sudoku puzzles.The mechanism to produce legal Sudoku grid will follow the requirements needed and meet all the constraints.A fitness function is designed to evaluate legal grids and GA will be tested for performance and time efficiency.The challenges lie on how GA will represent a Sudoku grid in the process and the effectiveness of its operators such as crossover and mutation.The results show how different population size can produce different solutions.The best performance is observed at 500 population size.The paper will conclude with an insight of this value and its significance to the knowledge acquisition in GA paradigm..…”
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Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem by Razip, H., Zakaria, M.N.

“…In Genetic Algorithm (GA), the prevalent approach to population initialization are heuristics and randomization. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…Last but not least, HKA has a very high dependency on the Gaussian assumption. The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…The algorithm includes (i) a population update strategy which improves the movement of hawks in the search space, (ii) a parameter adjusting strategy to control the transition between exploration and exploitation, and (iii) a population generating method in producing the initial candidate solutions. …”
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Iteration strategy and ts effect towards the performance of population based metaheuristics by Nor Azlina, Ab. Aziz, Nor Hidayati, Abdul Aziz, Azlan, Abd Aziz, Tasiransurini, Abdul Rahman, Wan Zakiah, Wan Ismail, Zuwairie, Ibrahim

“…The algorithms can be categorized based on number of agents, either single agent algorithms which are also known as single solution metaheuristics or multi agents algorithms, also known as population-based metaheuristics. …”
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Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

“…Like other population-based algorithms, WOA generate its population randomly during the exploration and exploitation phases, which could generate values far from the optimum solution or stuck the exploration around local optima. …”
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A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

“…In addition, the introduction of dynamic population control with polygamy selection processes enabled fast convergence to optimal solution and diversity in the population respectively.…”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…The second modification is the multiple population BH that is proposed as a generalization to the BH algorithm, in which the algorithm was not reliant upon the best solution but rather on a set of best solutions generated, called “MBH”. …”
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Fuzzy lifetime in genetic algorithm against premature convergence by Mohammad Jalali, Varnamkhasti, Lai, Soon Lee, Mohd Rizam, Abu Bakar, Nawfal, A. Mehdy

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