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Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique
Published 2008“…The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. …”
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A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism
Published 2008“…Multiple ant colonies optimization is an extension of the Ant Colony Optimization framework It offers a good opportunity to improve the ant colony optimization algorithms by encouraging the exploration of a wide area of the search space without losing the chance of exploiting the history of the search.This paper proposes a new multiple ant colonies optimization algorithm that is based on ant colony system and utilizes ave rage pheromone evaluation mechanism.The new algorithm divides the ants’ populations into multiple ant colonies and can be used to tackle large volume combinatorial optimization problems effectively. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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A new ant based rule extraction algorithm for web classification
Published 2011“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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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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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…The gray relational grade (GRG) performance metric and the Friedman test were used to evaluate the algorithm’s performance. The Taguchi-GRA method that produced the new values for the algorithm’s parameters was shown to be able to provide a better multi-objective generator maintenance scheduling (GMS) solution. …”
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Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…A multi-objective PACS algorithm based on sequential strategy which considers unit commitment and GMS problem separately is proposed to obtain solution for a proposed GMS model. …”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…In this research, a novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people was developed, it is called ‘‘Nomadic People Optimizer (NPO)’’. …”
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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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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Latin hypercube sampling Jaya algorithm based strategy for T-way test suite generation
Published 2020“…Jaya Algorithm (JA) is a new metaheuristic algorithm, has been used for solving different problems. …”
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Benchmark simulator with dynamic environment for job scheduling in grid computing
Published 2014“…Job scheduling algorithm has a significant influence on grid computing performance. …”
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An efficient innovative method to decrease routing table size in packet switched networks
Published 2013“…Taking into consideration the highly distributed character of networks, numerous multi-agent based algorithms, and particularly ant colony based algorithms, have been proposed in recent years. …”
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Unified strategy for intensification and diversification balance in ACO metaheuristic
Published 2017“…This intensification and diversification in Ant Colony Optimization (ACO) is the search strategy to achieve a trade-off between learning a new search experience (exploration) and earning from the previous experience (exploitation).The automation between the two processes is maintained using reactive search. …”
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Furrow and crypt detection using modified ant colony optimization for iris recognition / Zaheera Zainal Abidin
Published 2016“…Previous research has been done in selecting the unique iris features however it shows low accuracy performance. As a solution, to improve the accuracy performance, this research proposes a new approach called as Modified Ant Colony Optimization that uses ant colony algorithm which search for crypts and radial furrow. …”
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New optimization feature for the developed open cnc controller based on ISO 6983 and ISO 14649
Published 2021“…A new optimized system was developed based on open architecture control (OAC) technology and interpreted STEP-NC (Standard for the Exchange of Product Model Data) programming approaches. …”
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