TAILIEUCHUNG - Using hyper populated ant colonies for solving the TSP

The paper discusses the application of hyper populated ant colonies to the well-known traveling salesman problem (TSP). The ant colony optimization (ACO) approach offers reasonably good quality solutions for the TSP, but it suffers from its inherent non-determinism and as a consequence the processing time is unpredictable. The paper tries to mitigate the problem by a substantial increase in the number of used ants. | Vietnam J Comput Sci 2016 3 103-117 DOI s4O595-016-0059-z CrossMark REGULAR PAPER Using hyper populated ant colonies for solving the TSP Andrzej Sieminski 1 Received 19 October 2015 Accepted 18 February 2016 Published online 10 March 2016 The Author s 2016. This article is published with open access at Abstract The paper discusses the application of hyper populated ant colonies to the well-known traveling salesman problem TSP . The ant colony optimization ACO approach offers reasonably good quality solutions for the TSP but it suffers from its inherent non-determinism and as a consequence the processing time is unpredictable. The paper tries to mitigate the problem by a substantial increase in the number of used ants. This approach is called ant hyper population and it could be obtained by increasing the number of ants in a single colony assigning more than one colony to solve the same task or both. In all cases the level of nondeterminism decreases and thus the number iterations could be reduced. Parallel implementation of the ACO makes it possible to reduce drastically the processing time. The paper compares two ways of implementation of the parallelism using the sockets or the RMI remote method invocation mechanisms. The paper concentrates on the classical static version of the TSP but preliminary experiments indicate that such an approach could be even more useful for dynamic TPSs. Keywords Ant colony optimization Traveling salesmen problem Parallelization strategies for ACO Ant colony community ACC 11ntroduction The aim of the paper is to discuss the problem of optimizing the performance of the ant colony optimization ACO B Andrzej Sieminski . 1 Faculty of Computer Science and Management Wroclaw University of Technology Wroclaw Poland used for the traveling salesman problem TSP . Metaheuristics such as the ACO solve a complex problem by iteratively improving candidate solutions. They do not guarantee the .

• Quản trị kinh doanh
• Ant colony optimization
• Traveling salesmen problem
• Parallelization strategies for ACO
• Ant colony community
• Colony optimization
• International journal of computer science & communication networks
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• Hybrid ANT colony algorithm
• Distributed query optimization
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• Te optimization algorithm
• Ứng dụng thuật toán ACO
• Thuật toán ACO
• Chi phí cho dự án xây dựng
• Dự án xây dựng
• Quản lý dự án xây dựng
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• Bài giảng Tính toán tiến hóa
• Tính toán tiến hóa
• Ant colony optimization (ACO)
• Giải thuật tối ưu hóa bầy kiến
• Giải thuật tối ưu hóa bầy ong
• Bài toán tối ưu rời rạc
• Dynamic Optimization
• Neural Network
• Algorithm Convergence
• Multiobjective Optimization
• Ant Programming
• Green Manufacturing
• Colony Algorithms
• Meta heuristic
• Hybrid model
• Bacterial foraging algorithm
• Pair Wise exchange heuristic
• Ant Colony
• Optimization Toward
• Feature Selection
• Hardware Implementations
• Algorithmic Models
• Graphics Processing Units
• Electronic Engineering
• Fuszzy control
• Inverter power supply
• Inverter control
• Load adaptability
• Traffic routing
• Ant colony system
• Genetic algorithm
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• Luận văn Thạc sĩ
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• Synthetic biology
• Incorporating pseudoknot structures
• Giải thuật toán tối ưu bầy kiến
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