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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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2
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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Revisiting the pheromone evaluation mechanism in the interacted multiple ant colonies optimization framework
Published 2024Subjects: “…Ant colony optimization…”
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Interacted multiple ant colonies optimization framework: An experimental study of the evaluation and the exploration techniques to control the search stagnation
Published 2010“…Search stagnation is a serius prblem that all Ant Colony Optimization (ACO) algorithms suffer from regardless of their application domain. …”
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5
Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…In any metaheuristic, the parameter values strongly affect the efficiency of an algorithm’s search. This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. …”
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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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7
Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms
Published 2017“…One of BIAs, artificial bee colony (ABC) optimization algorithm, has shown excellent performance in many applications compared to other optimization algorithms. …”
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8
Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…The IEEE RTS 26, 32 and 36-unit dataset systems were used in the performance evaluation of the PACS algorithm. …”
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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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10
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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A new minimum pheromone threshold strategy (MPTS) for max-min ant system
Published 2009“…Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. …”
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Revisiting the pheromone evaluation mechanism in the interacted multiple ant colonies optimization framework
Published 2010“…Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. …”
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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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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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15
New optimization feature for the developed open cnc controller based on ISO 6983 and ISO 14649
Published 2021“…This research aims to minimize tool path airtime during machining of input ISO codes via an ant colony optimization algorithm. 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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Congestion management based optimization technique using bee colony
Published 2023Subjects: “…Bee colony algorithm…”
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An exploration technique for the interacted multiple ant colonies optimization framework
Published 2024Subjects: “…Ant colony optimization…”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
Published 2023“…This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. …”
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Power line faults classification by neural network train by Ant Colony Optimization
Published 2017“…Preparing a neural system is a procedure of finding the ideal set. An Ant Colony Optimization (ACO) is utilized to prepare with the neural systems. …”
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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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