Search Results - (( dynamic implementation ant algorithm ) OR ( java application optimization algorithm ))
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Ant colony optimization in dynamic environments
Published 2010“…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
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Thesis -
2
Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Monograph -
3
Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…One of the prominent intelligent algorithms is ant colony system (ACS) which is implemented widely to solve various types of scheduling problems. …”
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4
AntNet: a robust routing algorithm for data networks
Published 2004“…It is a combination of both static and dynamic routing algorithms. In this algorithm, a group of mobile agents (compared to real ants) form paths between source and destination nodes. …”
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Autonomous mobile robots path planning with integrative edge cloud-based ant colony optimization
Published 2025“…In recent years, Automated Mobile Robots (AMRs) have gained significant attention in industry and research applications, requiring efficient path-planning algorithms to optimize task performance. While widely adopted, conventional Ant Colony Optimization (ACO) algorithms suffer from low convergence rates and delays in task execution, particularly in dynamic environments due to insufficient exploration of this context. …”
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A trust aware secure ant colony optimization based routing algorithm for Internet of Things
Published 2023“…For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. …”
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Proceeding Paper -
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Scheduling Algorithm For Lot Movement in Semiconductor Wafer Fabrication
Published 2008“…Imitating the collective activities of ant colonies, an approach to constructing pheromone-based scheduling algorithm using Ant Colony Optimization for lot movement in semiconductor wafer fabrication process is propose to be implemented in SilTerra Malaysia.…”
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Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim
Published 2008“…The idea behind the adaptive job scheduling algorithm is the hybrid algorithms that consist of Ant Colony Optimization (ACO) and Tabu algorithms. …”
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Article -
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Benchmark simulator with dynamic environment for job scheduling in grid computing
Published 2014“…Characteristics of jobs and resources to be used in evaluating the performance of the scheduling algorithm must reflect the dynamic nature of real grid environment.Static models of jobs and resources cannot be used to generate jobs and resources in simulating the grid environment because of the dynamic nature of the grid.This paper presents a new graph representation of jobs and resources which is practical for hybrid metaheuristic model implementation such as ant colony optimization and genetic algorithm.A dynamic model that can generate jobs and resources similar to the jobs and resources in the real grid environment is also proposed.Jobs and resources may join in or drop out from the grid.Stochastic analysis is performed on the characteristics of jobs and resources.A simulator based on the dynamic expected time to compute, has been developed and can be used as a benchmark.The simulator can generate jobs and resources with the characteristics of jobs and resources in the real grid environment.This will facilitates the evaluation of dynamic job scheduling algorithm.…”
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Conference or Workshop Item -
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Ant lion optimizer for solving unit commitment with solar photovoltaic integration / Izni Nadhirah Sam’on
Published 2020“…The proposed ALO algorithm is able to identify the global optimum solution since the intensity of ants’ movement is adaptively decreased as the number of iterations increase. …”
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Thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment
Published 2018“…Dynamic task scheduling algorithms that can adjust to long-time changes and continue facilitating the provisioning of better QoS are necessary for cloud computing environment. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION
Published 2023“…In this paper, we study the advantages of fusing the Meta-Heuristic Bat Algorithm with Heuristic Optimization. We have implemented the Meta- Heuristic Bat Algorithm and tested it on a heterogeneous swarm. …”
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