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problem reduction graph model for discrete optimization problems
Zheng Yujun; Xue Jinyun
2010
Conference Name3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice
Source3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice
Pages190-194
Conference Date43979
Conference PlaceHuangshan, Anhui, China
Publish PlaceUnited States
ISBN9780770000000
Department(1) State Key Lab of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) Provincial Key Lab of High Performance Computing, Jiangxi Normal University, Nanchang, China; (3) Graduate University, Chinese Academy of Sciences, Beijing, China
English AbstractThe paper proposes the problem reduction graph (PRG), an abstract model for discrete optimization problems which uses structural decomposition to reduce problem complexity and constructs the recurrence relations between the problem and its subproblems. We develop several important algorithm patterns for PRG construction, each leading to a special class of concrete problem-solving algorithms in a systematic way. The model supports logical transformation from specifications to algorithmic programs by deductive inference, and thus significantly promotes the automation and reusability of algorithm design. © 2010 IEEE.
KeywordAlgorithms Combinatorial Optimization Computer Software Reusability Inference Engines Reusability
SponsorshipChinese Academy of Sciences (CAS); Dep. Manage. Sci. Natl. Nat. Sci. Found. China (NSFC); Academy of Mathematics and Systems Science of CAS; Institute of Systems Science of CAS; Centre for Forecasting Science (CEFS) of CAS
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8860
Collection基础软件与系统重点实验室
Recommended Citation
GB/T 7714
Zheng Yujun,Xue Jinyun. problem reduction graph model for discrete optimization problems[C]. United States,2010:190-194.
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