Search Results - (( _ application ((ant algorithm) OR (means algorithm)) ) OR ( its application using algorithm ))*
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…The main idea in this algorithm is the indirect communication between the ants which is established by the means of pheromones in finding the shortest path between their nest and food [14]. …”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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Enhancing Solutions Of Capacity Vehicle Routing Problem Based On An Improvement Ant Colony System Algorithm
Published 2019“…The paper aims to discover an optimal route for VRP by using Improvement Ant Colony System Algorithm (IACS). …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Metaheuristic algorithms have been adapted in various engineering applications due to their efficiencies in solving complex and larger real-life optimization problems. …”
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Optimization of multi-holes drilling toolpath using tiki-taka algorithm
Published 2024“…A computational experiment was conducted on 12 test problems across small, medium, and large problem categories using the TTA, then compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Crayfish Optimization Algorithm (COA), and Geometric Mean Optimizer (GMO). …”
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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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Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid
Published 2013“…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid
Published 2013“…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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Ant colony optimization algorithm for load balancing in grid computing
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New heuristic function in ant colony system for job scheduling in grid computing
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QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs)
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Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP).
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article
