Search Results - (( simulation optimization means algorithm ) OR ( using optimization window algorithm ))
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Optimized crossover genetic algorithm for vehicle routing problem with time windows
Published 2010“…Conclusion/Recommendations: This study presented a genetic algorithm for solving vehicle routing problem with time windows using an optimized crossover operator. …”
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
Published 2022“…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks
Published 2016“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows
Published 2022“…The proposed algorithm was evaluated using benchmark datasets comprising 56 VRPTW instances and 56 Pickup and Delivery Problems with Time Windows (PDPTW). …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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Determining optimal location of static VAR compensator by means of genetic algorithm
Published 2011“…This method is employed to optimize the stability of power system by means of maximizing distance to collapse point. …”
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Finally, the role of the coordinator is to select a subset of patients from the window and pass them to the optimization algorithm. …”
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Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms
Published 2016“…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm
Published 2014“…Detection is provided by using statistical analysis in each window, then the appropriate replacement for the noisy pixel is conducted from given values inside the current window or adjacent reconstructed pixels based on mean calculation and also, for very high density of noise which density of noise is bigger than 80%, the reconstruction is based on a recursive approach. …”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…The analytical results are validated through simulation. Finally, extensive simulations have been done to evaluate the performance of the proposed algorithm for various choices of optimal q-values. …”
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Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean
Published 2007“…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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Modified K-Nearest Neighborhood Algorithm For Optimal Selection Of Distribution Centre In The Disaster Relief Operation
Published 2024thesis::master thesis -
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Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm
Published 2016“…This signifies that the training was successful based on the fitted values of the window size. Thus the proposed model trained with the CS algorithm provides a high convergence rate to the true global minimum and a better optimal solution. …”
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Single Step Multivariate Solar Power Forecasting using Adaptive Learning Rate LSTM Model with Optimized Window Size
Published 2024Conference Paper -
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Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms
Published 2016“…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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