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multiobjectiveoptimizationofthedistributedpermutationflowshopschedulingproblemwithtransportationandeligibilityconstraints 期刊论文
journaloftheoperationsresearchsocietyofchina, 2018, 卷号: 6, 期号: 3, 页码: 391
Authors:  Cai Shuang;  Yang Ke;  Liu Ke
Favorite  |  View/Download:97/0  |  Submit date:2020/01/10
Multi-objective Optimization of the Distributed Permutation Flow Shop Scheduling Problem with Transportation and Eligibility Constraints 期刊论文
Journal of the Operations Research Society of China,, 2018, 卷号: 6, 期号: 3, 页码: 391
Authors:  Cai Shuang;  Yang Ke;  Liu Ke
Favorite  |  View/Download:72/0  |  Submit date:2021/01/14
Tax Evasion: Models with Self-Audit 期刊论文
JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2008, 卷号: 21, 期号: 4, 页码: 487-518
Authors:  Xiao, Tingting;  Liu, Ke;  Lai, Kin Keung
Favorite  |  View/Download:66/0  |  Submit date:2018/07/30
Existence and uniqueness of the solution  self-audit  static model  tax evasion  two-period model  
Optimal ordering in a dual-supplier system with demand forecast updates 期刊论文
PRODUCTION AND OPERATIONS MANAGEMENT, 2003, 卷号: 12, 期号: 1, 页码: 30-45
Authors:  Yan, HM;  Liu, K;  Hsu, A
Favorite  |  View/Download:78/0  |  Submit date:2018/07/30
supply chain management  demand information revisions  forecasting  
A note on optimality conditions for continuous-time Markov decision processes with average cost criterion 期刊论文
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2001, 卷号: 46, 期号: 12, 页码: 1984-1989
Authors:  Guo, XP;  Liu, K
Favorite  |  View/Download:65/0  |  Submit date:2018/07/30
average cost criterion  continuous-time Markov decision processes (MDPs)  optimal stationary policies  optimality inequality  
Nonhomogeneous Markov decision processes with Borel state space - The average criterion with nonuniformly bounded rewards 期刊论文
MATHEMATICS OF OPERATIONS RESEARCH, 2000, 卷号: 25, 期号: 4, 页码: 667-678
Authors:  Guo, XP;  Liu, JY;  Liu, K
Favorite  |  View/Download:73/0  |  Submit date:2018/07/30
nonhomogeneous Markov decision processes  average reward criterion  optimality equations  epsilon(>= 0)-optimal policies  rolling horizon algorithm