Search Results - (( linear programming model algorithm ) OR ( java simulation optimization algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…This approach tunes the parameters of the linear programming models that are used in the other algorithms by using a dynamic element. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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An Integer Linear Programming model and Adaptive Genetic Algorithm approach to minimize energy consumption of Cloud computing data centers
Published 2018“…This paper focuses on the development of a dynamic task scheduling algorithm by proposing an Integer Linear Programming (ILP) model that minimizes the energy consumption in a Cloud data center. …”
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Solving Sudoku puzzles in Binary Integer Linear Programming using Branch and Bound algorithm / Ahida Waliyyah Ahmad Fuad
Published 2024“…This study explores the application of a Binary Integer Linear Programming (BILP) model combined with the Branch and Bound (B&B) algorithm to solve Sudoku puzzles. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2023“…Biomass; Catalysis; Digital storage; Gasification; Gaussian distribution; Hydrogen production; Learning algorithms; Lime; Palm oil; Quadratic programming; Regression analysis; Sensitivity analysis; Synthesis gas; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Non-linear response; Performance; Quadratic modeling; Renewable energies; Support vectors machine; Syn gas; Support vector machines…”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling
Published 2018“…Objectives: In this study, multiple linear regression model was calculated by using SAS programming language based on computational statistics which considered combination of robust regression, bootstrap, weighted data, Bayesian, and fuzzy regression method. …”
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Proceeding Paper -
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A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms
Published 2023“…Decision making; Dynamic programming; Linear programming; Nonlinear programming; Operating costs; 'current; Energy productions; Floodings; Meta-heuristics algorithms; Optimal reservoir operations; Optimizing energy; Reservoir operation; Reservoir operation optimizations; Traditional models; Water scarcity; Reservoirs (water)…”
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