Discrete State Transition Algorithm for Unconstrained Integer Optimization Problems
arXiv:1209.4199 · doi:10.1016/j.neucom.2015.08.041
Abstract
A recently new intelligent optimization algorithm called discrete state transition algorithm is considered in this study, for solving unconstrained integer optimization problems. Firstly, some key elements for discrete state transition algorithm are summarized to guide its well development. Several intelligent operators are designed for local exploitation and global exploration. Then, a dynamic adjustment strategy ``risk and restoration in probability" is proposed to capture global solutions with high probability. Finally, numerical experiments are carried out to test the performance of the proposed algorithm compared with other heuristics, and they show that the similar intelligent operators can be applied to ranging from traveling salesman problem, boolean integer programming, to discrete value selection problem, which indicates the adaptability and flexibility of the proposed intelligent elements.
14 pages, 13 figures
References in corpus (6)
- State Transition Algorithm
- Nonlinear system identification and control using state transition algorithm
- Optimal Design of Water Distribution Networks by Discrete State Transition Algorithm
- Initial Version of State Transition Algorithm
- A new transformation into State Transition Algorithm for finding the global minimum
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Cited by in corpus (5)
- A Statistical Study on Parameter Selection of Operators in Continuous State Transition Algorithm
- A dynamic state transition algorithm with application to sensor network localization
- A matlab toolbox for continuous state transition algorithm
- A Comparative Study of STA on Large Scale Global Optimization
- Multiagent based state transition algorithm for global optimization