Search Results - (( solution population using algorithm ) OR ( program implementation using algorithm ))
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1
Implementation Of Hardware Software Partitioning In Embedded System
Published 2018“…The parameter setting is used for both algorithms is 15 number of task/node, 500 maximum number of iteration, 100 no of particles/population size and the pre-defined hardware and software area and execution time for each task as the input of the algorithms. …”
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2
Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution
Published 2017“…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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Article -
3
Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong
Published 2018“…The computational results show that the algorithms which implement this new formulation are able to produce better solutions. …”
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4
Genetic Algorithm for vehicle routing problem / W.Nurfahizul Ifwah W.Alias, Mohd Shaiful Sharipudin and Shamsunarnie Mohamed Zukri.
Published 2012“…They are also robust and effective algorithms that are computationally simple and easy to implement.…”
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Research Reports -
5
Sub-route reversal repair mechanism and differential evolution for urban transit network design problem
Published 2017“…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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6
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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7
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]
Published 2015“…GA implementation on TSP is done by using Microsoft C++ Programming. …”
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10
Using genetic algorithms to optimise land use suitability
Published 2012“…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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11
Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M...
Published 2016“…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...
Published 2017“…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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Book Section -
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Hybridization solution of electrical energy demand response and forecasting program by using PSO-LSSVM technique
Published 2023“…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
Published 2010“…Algorithms are used to find the solutions through the computer program. …”
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Monograph -
15
Multi-population Genetic Algorithm for Rich Vehicle Routing Problems
Published 2020“…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
Published 2017“…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
Published 2010“…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
Published 2018“…In Genetic Algorithm (GA), the prevalent approach to population initialization are heuristics and randomization. …”
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Article -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…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
Published 2012“…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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