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Dependent-chance goal programming and its genetic algorithm based approach
Liu, BD
1996-10-01
Source PublicationMATHEMATICAL AND COMPUTER MODELLING
ISSN0895-7177
Volume24Issue:7Pages:43-52
AbstractThis paper develops a general formulation of dependent-chance goal programming (DCGP) which is an extension of stochastic goal programming in a complex stochastic system, and gives an example of water allocation and supply to show the application of DCGP. A genetic algorithm based approach is also presented to solve such a model. DCGP is available to the systems in which there are multiple stochastic inputs and multiple outputs with their own reliability levels. The characteristic of DCGP is that the chances of some probabilistic goals are dependent, i.e., the goals cannot be considered in isolation or converted to their deterministic equivalents. Finally, Monte Carlo simulation is also discussed for calculating the chance functions in complex stochastic constraints.
Keywordstochastic programming goal programming dependent-chance goal programming genetic algorithm
Language英语
WOS Research AreaComputer Science ; Mathematics
WOS SubjectComputer Science, Interdisciplinary Applications ; Computer Science, Software Engineering ; Mathematics, Applied
WOS IDWOS:A1996VN51000004
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/28818
Collection中国科学院数学与系统科学研究院
AffiliationCHINESE ACAD SCI,INST SYST SCI,BEIJING 100080,PEOPLES R CHINA
Recommended Citation
GB/T 7714
Liu, BD. Dependent-chance goal programming and its genetic algorithm based approach[J]. MATHEMATICAL AND COMPUTER MODELLING,1996,24(7):43-52.
APA Liu, BD.(1996).Dependent-chance goal programming and its genetic algorithm based approach.MATHEMATICAL AND COMPUTER MODELLING,24(7),43-52.
MLA Liu, BD."Dependent-chance goal programming and its genetic algorithm based approach".MATHEMATICAL AND COMPUTER MODELLING 24.7(1996):43-52.
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