A Novel Fused Optimization Algorithm of Genetic Algorithm and Ant Colony Optimization [PDF]
Mathematical Problems in Engineering, 2016 A novel fused algorithm that delivers the benefits of both genetic algorithms (GAs) and ant colony optimization (ACO) is proposed to solve the supplier selection problem. The proposed method combines the evolutionary effect of GAs and the cooperative effect of ACO.
FuTao Zhao +3 more
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Intrusion Detection and Classification Using Ant Colony Optimization Algorithm [PDF]
المجلة العراقية للعلوم الاحصائية, 2013 Studies of ant colonies have contributed in abundance to the set of intelligent algorithms. The modeling of pheromone depositing by ants in their search for the shortest paths to food sources resulted in the development of shortest path optimization ...
Mafaz Mohsin Khalil Al-Anezi +3 more
doaj +1 more source
An Improvement of a Mapping Method Based on Ant Colony Algorithm Applied to Smart Cities
Applied Sciences, 2022 The ant colony algorithm has been widely used in the field of data analysis of smart cities. However, the research of the traditional ant colony algorithm is more focused on one-to-one scenarios and there is insufficient research on many-to-one scenarios.
Kaiming Xu +3 more
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Routing Algorithm for Micro-Nano-Satellite Based on Q-Learning Quantum Ant Colony [PDF]
Jisuanji gongcheng, 2022 In micro-nano-satellite networks, the traditional ant colony routing algorithm cannot guarantee data transmission security and the quality of service of network businesses simultaneously.Moreover, it is easy to fall into local optimal solution, and the ...
ZHANG Ran, GAO Yingxue, ZHAO Yu, DING Yuanming
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Self-adaptive hybrid genetic algorithm using an ant-based algorithm [PDF]
, 2014 The pheromone trail metaphor is a simple and effective way to accumulate the experience of the past solutions in solving discrete optimization problems. Ant-based optimization algorithms have been successfully employed to solve hard optimization problems.
Aref, Ibrahim A. +2 more
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Feature Optimization of EEG Signals Based on Ant Colony Algorithm [PDF]
BIO Web of Conferences, 2023 EEG signal can be understood as a kind of bioelectrical signal, which can reflect emotional information when the body is in different emotional states. However, the data collected are often high-dimensional.
Shengjie Zhang, Rongkai Pan, Guanglu Liu
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Improving ant colony optimization algorithm with epsilon greedy and Levy flight
Complex & Intelligent Systems, 2020 Ant colony optimization (ACO) algorithm is a meta-heuristic and reinforcement learning algorithm, which has been widely applied to solve various optimization problems.
Yahui Liu, Buyang Cao, Hehua Li
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Optimal Unit Commitment with Ant Colony Algorithm [PDF]
Computational Research, 2014 This paper presents an improved ant colony search algorithm that is suitable for solving unit commitment (UC) problems. Ant colony algorithm (ACA) is a meta-heuristic technique for solving hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback, distributed computation as well as ...
Majid Alizadeh Moghadam +1 more
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Comparison of Adaptive Ant Colony Optimization for Image Edge Detection of Leaves Bone Structure
Emitter: International Journal of Engineering Technology, 2018 Leaf bone structure has a characteristic that can be used as a reference in digital image processing. One form of digital image processing is image edge detection. Edge detection is the process of extracting edge information from an image.
Febri Liantoni +2 more
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Investigating Evaluation Measures in Ant Colony Algorithms for Learning Decision Tree Classifiers [PDF]
, 2015 Ant-Tree-Miner is a decision tree induction algorithm that is based on the Ant Colony Optimization (ACO) meta- heuristic. Ant-Tree-Miner-M is a recently introduced extension of Ant-Tree-Miner that learns multi-tree classification models.
Abdelbar, Ashraf M. +2 more
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