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Discrete state transition algorithm for unconstrained integer optimization problems

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周晓君 cover
周晓君 (Xiaojun Zhou) *
D
David Yang Gao
C
Chunhua Yang
W
Weihua Gui
DOI:10.1016/j.neucom.2015.08.041delete
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Abstract

Abstract

En 中文
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. (C) 2015 Elsevier B.V. All rights reserved.
Keywords:
State transition algorithm
Integer optimization
Traveling salesman problem
Maximum cut problem
Discrete value selection
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Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

Organization

C
Central South University
Scholars:
10.0W
Papers: 7.2W
Citations: 10.9W
F
Federation University Australia
Scholars:
2.0K
Papers: 2.3K
Citations: 17
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