Search Results - (( java application a algorithm ) OR ( dynamic using 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“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Article -
2
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Monograph -
3
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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Thesis -
4
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023“…Genetic algorithms are powerful optimizing techniques that are used successfully to solve problems in many different disciplines. …”
Conference paper -
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Resource management in grid computing using ant colony optimization
Published 2011“…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism.The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element.The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job.EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form.The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. …”
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Monograph -
6
Visdom: Smart guide robot for visually impaired people
Published 2025“…An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Final Year Project / Dissertation / Thesis -
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Ant colony optimization in dynamic environments
Published 2010“…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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8
Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators
Published 2024“…Interestingly, the manipulator's behaviours using the spiral dynamics algorithm for PID controller tuning were superior to those using alternative methods. …”
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Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment
Published 2021“…This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. The particle swarm optimization and spiral dynamic algorithm are used for enhanced performance of the IT2FLC by finding optimised values for input and output controller gains and parameter values of IT2FLC membership function as comparison purpose in order to identify better solution for the system. …”
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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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Final Year Project / Dissertation / Thesis -
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution…”
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14
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Monograph -
15
Spiral-sooty tern optimization algorithm for dynamic modelling of a twin rotor system
Published 2022“…For solving a real-world problem, the proposed SSTA algorithm in comparison to STOA is applied to optimize parameters of a linear Autoregressive-Exogenous (ARX) dynamic model for a twin rotor system. …”
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Conference or Workshop Item -
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Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system
Published 2022“…Spiral Dynamic Algorithm (SDA) is a group-based optimization algorithm formulated based on the concept of a natural spiral phenomenon on earth. …”
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New algorithm for autonomous dynamic path planning in real-time intelligent robot car
Published 2017“…Different algorithms have been used to address this problem by considering the optimal path with minimum cost; however, these algorithms did not consider the execution time to find such path. …”
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Therefore, it treats PASP as a multi-objective dynamic optimization of a useful solution. NSGA-II is guaranteed 0.96 percent dominance over NSGA-II and 100 percent dominance of all other algorithms.…”
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Article -
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…In addition, the two algorithms have achieved a remarkable improvement from the adaptation of dynamic parameterization. …”
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Thesis -
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