Search Results - (( solution population _ algorithm ) OR ( program implementation using algorithm ))

Implementation Of Hardware Software Partitioning In Embedded System by Mohd Nor, Masyirah

“…Both of the algorithms are achieve the same best cost which is 169.6022 and the optimum solution proposed by both algorithms are nine tasks should be run in hardware and six tasks should be run in software. …”
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Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution by Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, Hamed, Raed Ibraheem, A. Mostafa, Salama, Ahmed Ibrahim, Dheyaa, Jameel, Humam Khaled, Alallah, Ahmed Hamed

“…The structure of the algorithm is designed so that the program does not require a large database to store the population, which speeds up the implementation of the program execution to obtain the solution; secondly, the algorithm has proven its success in solving the problem and finds a shortest route. …”
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Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong by Lily , Wong

“…The computational results show that the algorithms which implement this new formulation are able to produce better solutions. …”
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Genetic Algorithm for vehicle routing problem / W.Nurfahizul Ifwah W.Alias, Mohd Shaiful Sharipudin and Shamsunarnie Mohamed Zukri. by W.Alias, W.Nurfahizul Ifwah, Sharipudin, Mohd Shaiful, Mohamed Zukri, Shamsunarnie

“…They are also robust and effective algorithms that are computationally simple and easy to implement.…”
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Sub-route reversal repair mechanism and differential evolution for urban transit network design problem by Tarajo, Buba Ahmed

“…From the literature of UTNDP, the most widely used metaheuristic is the genetic algorithm, at the expense of other population-based metaheuristics. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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Examination invigilation timetable using Genetic Algorithm / Mohamad Fakhrullah Ibrahim by Ibrahim, Mohamad Fakhrullah

“…GA employs key steps, including population initialization, fitness evaluation, selection, crossover, and mutation, to iteratively improve solutions. …”
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New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.] by Alias, Fadzilawani Astifar, Shamsuddin, Maisurah, Mohamed, Siti Asmah, Mahlan, Siti Balqis

“…GA implementation on TSP is done by using Microsoft C++ Programming. …”
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Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Mohammed, Daw Saleh Sasi

“…Contrary to the conventional approaches, which mainly rely on dispatching of each limited energy unit (LEU) in sequential order, the proposed algorithm comprising with optimization technique is used as an alternative for performing LEU dispatch; which has a tangible impact to improve and increase the AUC value. …”
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Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Sasi Mohamme, Daw Saleh

“…Contrary to the conventional approaches, which mainly rely on dispatching of each limited energy unit (LEU) in sequential order, the proposed algorithm comprising with optimization technique is used as an alternative for performing LEU dispatch; which has a tangible impact to improve and increase the AUC value. …”
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Hybridization solution of electrical energy demand response and forecasting program by using PSO-LSSVM technique by Ali, Amira Noor Farhanie, Sulaima, Mohamad Fani, Tahir, Musthafah Mohd., Razak, Intan Azmira Wan Abdul, Kadir, Aida Fazliana Abdul, Rahman, Zulkifli Ab.

“…The study's findings will assist manufacturers in transitioning to the ETOU tariff and contribute to the national DSM initiative program. Future research may examine other optimization algorithms and load forecasting models to refine ETOU tariff rate price reduction strategies and define available load for specific load management strategies.…”
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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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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment by Shen, jiazheng, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan, Wang, Xinming

“…The experiment verified that this strategy can approach the optimal solution more closely during the population convergence process, and compared it with traditional Multi TSP algorithms and single function multi-objective Multi TSP algorithms. …”
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Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

“…The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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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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Implementation of autonomous vehicle navigation algorithms using event-driven programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

“…The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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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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