Search Results - ((((((acs algorithm) OR (ant algorithm))) OR (based algorithm))) OR (_ algorithm))
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1
Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…The algorithms are ACS(GA), ACS+GA, ACS(TS), and ACS+TS. …”
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2
Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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3
Balancing exploration and exploitation in ACS algorithms for data clustering
Published 2019“…ACO for clustering (ACOC) is an ant colony system (ACS) algorithm inspired by the foraging behavior of ants for clustering tasks. …”
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4
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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5
Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. …”
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6
An enhanced ant colony system algorithm for dynamic fault tolerance in grid computing
Published 2020“…Ant colony system (ACS), a variant of ant colony optimization (ACO), is one of the promising algorithms for fault tolerance due to its ability to adapt to both static and dynamic combinatorial optimization problems. …”
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7
Improvement DACS3 Searching Performance using Local Search
Published 2009“…Several versions of metaheuristic ACOs’ have been developed through several improvement processes to produce better algorithm. Past research has proposed a Dynamic Ant Colony System with Three Level Updates (DACS3) algorithm that embedding a Malaysian House Red Ant behavior into current ACS. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Modified ACS centroid memory for data clustering
Published 2019“…Ant Colony Optimization for Clustering (ACOC) is a swarm algorithm inspired from nature to solve clustering issues as optimization problems. …”
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10
Strategies DACS3 Increasing its Performances
Published 2009“…Ant Colony System (ACS) is the most popular algorithm used to find a shortest path solution in Traveling Salesman problem (TSP). …”
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11
FINDING SHORTEST PATH FOR DYNAMIC PUTTING PROBLEM USING ANT COLONY OPTIMISATION
Published 2005“…Specifically. this thesis is intended to develop a system that can display the shortest path by the used of two algorithm in ACO which were Ant System (AS) and Ant Colony System (ACS). …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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13
New heuristic function in ant colony system for the travelling salesman problem
Published 2012“…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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14
New heuristic function in ant colony system algorithm
Published 2012“…NP-hard problem can be solved by Ant Colony System (ACS) algorithm.However, ACS suffers from pheromone stagnation problem, a situation when all ants converge quickly to one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic value to calculate the probability of choosing the next node.However, the heuristic value is not updated throughout the process to reflect new information discovered by the ants.This paper proposes a new heuristic function for the Ant Colony System algorithm that can reflect new information discovered by ants.The credibility of the new function was tested on travelling salesman and grid computing problems.Promising results were obtained when compared to classical ACS algorithm in terms of best tour length for the travelling sales-man problem. …”
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15
Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
Published 2015“…Hybrid metaheuristic algorithms have the ability to produce better solution than stand-alone approach and no algorithm could be concluded as the best algorithm for scheduling algorithm or in general, for combinatorial problems.This study presents the low and high level hybridization of ant colony system and genetic algorithm in solving the job scheduling in grid computing.Two hybrid algorithms namely ACS(GA) as a low level and ACS+GA as a high level are proposed.The proposed algorithms were evaluated using static benchmarks problems known as expected time to compute model. …”
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16
Scheduling jobs in computational grid using hybrid ACS and GA approach
Published 2014“…Metaheuristics algorithms show very good performance in solving various job scheduling problems in computational grid systems.However, due to the complexity and heterogeneous nature of resources in grid computing, stand-alone algorithm is not capable to find a good quality solution in reasonable time.This study proposes a hybrid algorithm, specifically ant colony system and genetic algorithm to solve the job scheduling problem.The high level hybridization algorithm will keep the identity of each algorithm in performing the scheduling task.The study focuses on static grid computing environment and the metrics for optimization are the makespan and flowtime.Experiment results show that the proposed algorithm outperforms other stand-alone algorithms such as ant system, genetic algorithms, and ant colony system for makespan.However, for flowtime, ant system and genetic algorithm perform better.…”
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17
Embedding Malaysian House Red Ant Behavior into an Ant Colony System
Published 2008“…This research aims to improve the algorithm by embedding individual Malaysian House Red Ant behavior into ACS. …”
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18
An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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19
Fault tolerance grid scheduling with checkpoint based on ant colony system
Published 2017“…The proposed algorithm is compared with other relevant algorithms to measure the performance in terms of execution time, success rate and average processing time. …”
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DACS3:Embedding Individual Ant Behavior in Ant Colony System
Published 2008“…Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). …”
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