Results 111 to 120 of about 8,500 (224)

An ant system algorithm for automated trajectory planning

, 2010
The paper presents an Ant System based algorithm to optimally plan multi-gravity assist trajectories. The algorithm is designed to solve planning problems in which there is a strong dependency of one decision one all the previously made decisions. In the
Vasile, M., Ceriotti, M.
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Robot path planning based on obstacle avoidance optimization and improved ant colony algorithm

Xi'an Gongcheng Daxue xuebao
Aimed at the problems of slow convergence speed and redundant planning paths in the processing of path planning by ant colony algorithm, an improved ant colony algorithm based on obstacle avoidance information and fast optimization search strategy was ...
HE Xingshi, CHEN Huiyuan
doaj   +1 more source

Fuzzy Dynamic Parameter Adaptation in ACO and PSO for Designing Fuzzy Controllers: The Cases of Water Level and Temperature Control

Advances in Fuzzy Systems, 2018
A novel approach applied to Particle Swarm Optimization (PSO) and Ant Colony Optimization is presented. The main contribution of this work is the use of fuzzy systems to dynamically update the parameters for the ACO and PSO algorithms. In the case of ACO,
Fevrier Valdez, Juan Carlos Vazquez, Fernando Gaxiola   +2 more
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Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants

Engineering Applications of Computational Fluid Mechanics, 2020
A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors.
Shahaboddin Shamshirband, Meisam Babanezhad, Amir Mosavi, Narjes Nabipour, Eva Hajnal, Laszlo Nadai, Kwok-Wing Chau   +6 more
doaj   +1 more source

A hybrid artificial algae and ant colony optimization algorithm for combinatorial problems [PDF]

PeerJ Computer Science
The Traveling Salesman Problem (TSP) is a classical Nondeterministic Polynomial time (NP)-hard optimization problem that continues to inspire new metaheuristic designs.
Mustafa Altıok
doaj   +2 more sources

A hierarchical multi-label classification ant colony algorithm for protein function prediction [PDF]

, 2010
This paper proposes a novel ant colony optimisation (ACO) algorithm tailored for the hierarchical multi-label classification problem of protein function prediction.
Otero, Fernando E.B., Colin G. Johnson, Johnson, Colin G., Alex A. Freitas, Freitas, Alex A., Fernando E. B. Otero   +5 more
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Improved adaptive ant colony algorithm by incorporating multiple strategies

Nantong Daxue xuebao. Ziran kexue ban
To address the problems of slow convergence and local optima entrapment in the ant colony algorithm(ACO), this paper proposes an improved ant colony algorithm(IACO) integrating multiple strategies.
LIU Yutong; LI Yuan; ZHENG Xinyu
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Intercluster Ant Colony Optimization Algorithm for Wireless Sensor Network in Dense Environment

International Journal of Distributed Sensor Networks, 2014
Wireless sensor networks have grown rapidly with the innovation in Information Technology. Sensor nodes are distributed and deployed over the area for gathering requisite information. Sensor nodes possess a negative characteristic of limited energy which
Jung-Yoon Kim, Tripti Sharma, Brijesh Kumar, G. S. Tomar, Karan Berry, Won-Hyung Lee   +5 more
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Ant-Colony Based Near-ML Space-Time Multiuser Detection for the STBC Assisted DS-CDMA Uplink

, 2010
In this contribution, a novel Ant Colony Optimization (ACO) based Space-Time (ST) Multiuser Detection (MUD) algorithm was proposed in order to improve the Bit Error Ratio (BER) versus Signal-to-Noise Ratio (SNR) performance achieved by the Space-Time ...
Yang, Lie-Liang, Chong Xu, Lie-Liang Yang, Xu, Chong, Hanzo, Lajos, Lajos Hanzo   +5 more
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Rigorous analyses for the combination of ant colony optimization and local search [PDF]

, 2008
Also published as a journal article: Lecture notes in computer science, 2008; 5217:132-143Ant colony optimization (ACO) is a metaheuristic that produces good results for a wide range of combinatorial optimization problems.
PELLEGRINI P, Witt, Carsten, Neumann, Frank, Andrea Ellero, ELLERO A., Paola Pellegrini, Witt, C., Neumann, F., Sudholt, D., Sudholt, Dirk, PELLEGRINI, Paola, ELLERO, Andrea   +11 more
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