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On the Faster Ant Colony Optimization Algorithm
2009 Fifth International Conference on Natural Computation, 2009The pheromone trails in ACO are used to reflect the ants’ search experience, so the quality of the pheromone is crucial to the success of ACO. The main factors affecting the quality of the pheromone include the strategy of updating the pheromone and the quality of the constructed solutions.
Yingzhou Bi, Lixin Ding, Jianbo Lu
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Optimal Disk Scheduling Based On Ant Colony Optimization Algorithm
2006Disk scheduling problem has theoretical interest and practical importance since, the processor speed and memory capacity have been progressing several times faster than disk speed. More efficient disk usage methods have been needed because of the slow evolution in disk speed technology.
ÖKDEM, Selçuk, KARABOĞA, Derviş
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Ant colony algorithm based Controls' arrangement optimization
2010 2nd International Conference on Advanced Computer Control, 2010For the arrangement of Controls in human-machine interface based on the multiple operating conditions, the following factors should be considered: the design principles such as the importance of Controls, operating frequency, operating sequence and relativity between the Controls, and the total motion distance of the operator's hand. The arrangement in
null Shengyuan Yan +3 more
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Solving Continuous Optimization Using Ant Colony Algorithm
2009 Second International Conference on Future Information Technology and Management Engineering, 2009One shortcoming of ant colony optimization is that it can not be applied on continuous optimization problems directly. In this paper we propose a new approach for solving continuous optimization problems using ant colony algorithm. While the method maintains the framework of the classical ant colony algorithm, it replaces the discrete frequency in the ...
Ling Chen, Haiying Sun, Shu Wang
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Improved Strategies of Ant Colony Optimization Algorithms
2012Ant Colony Optimization (ACO) algorithms, inspired by the foraging behavior of real ants, have achieved great success in tackling discrete combinational optimization problems. Since the first ant algorithm—Ant System was introduced in early 1990s, various improved versions of ant algorithms have been proposed and most of them share similar improving ...
Ping Guo, Zhujin Liu, Lin Zhu
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Information Hiding Using Ant Colony Optimization Algorithm
International Journal of Technology Diffusion, 2011This paper aims to find an effective and efficient information hiding method used for protecting secret information by embedding it in a cover media such as images. Finding the optimal set of the image pixel bits to be substituted by the secret message bits, such that the cover image is of high quality, is a complex process and there is an exponential ...
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A New Multi-ant Colony Optimization Algorithm
2012This paper introduces the basic ant colony algorithm, the model and its problems in the process of solving the TSP. Because the basic ant colony algorithm to search for to a certain extent, all individuals found the same solutions n in exactly, it can not search the solution space in further, it is not conducive to find better solutions.
He Yueshun, Du Ping
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A Novel Quantum Ant Colony Optimization Algorithm
2007Ant colony optimization (ACO) is a technique for mainly optimizing the discrete optimization problem. Based on transforming the discrete binary optimization problem as a "best path" problem solved using the ant colony metaphor, a novel quantum ant colony optimization (QACO) algorithm is proposed to tackle it.
Ling Wang, Qun Niu, Minrui Fei
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Path planning optimization of indoor mobile robot based on adaptive ant colony algorithm
Computers and Industrial Engineering, 2021Yuanyuan Wu
exaly