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Volumn 18, Issue 4, 2007, Pages 1165-1186

Successive linear approximation solution of infinite-horizon dynamic stochastic programs

Author keywords

Cutting planes; Dynamic programming; Infinite horizon; Linear approximation; Stochastic programming

Indexed keywords

CONVEX OBJECTIVES; CUTTING PLANES; INFINITE HORIZON; LINEAR APPROXIMATION; LINEAR APPROXIMATION METHODS; LINEAR APPROXIMATIONS; LINEAR DYNAMICS; OPTIMAL VALUE FUNCTIONS; VALUE FUNCTIONS;

EID: 56749153647     PISSN: 10526234     EISSN: None     Source Type: Journal    
DOI: 10.1137/060665506     Document Type: Article
Times cited : (7)

References (16)
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    • H. BENITEZ-SILVA, G. HALL, G. J. HITSCH, G. PAULETTO, AND J. RUST, A Comparison of Discrete and Parametric Approximation Methods for Continuous-State Dynamic Programming problems, Reseach report, Department of Economics, Yale University, New Haven, CT, 2000 (also Working Paper No. 24, Computation in Economics and Finance, Society for Computational Economics, 2000).
    • H. BENITEZ-SILVA, G. HALL, G. J. HITSCH, G. PAULETTO, AND J. RUST, A Comparison of Discrete and Parametric Approximation Methods for Continuous-State Dynamic Programming problems, Reseach report, Department of Economics, Yale University, New Haven, CT, 2000 (also Working Paper No. 24, Computation in Economics and Finance, Society for Computational Economics, 2000).
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  • 7
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    • L. A. KORF, Approximating infinite horizon stochastic optimal control in discrete time with constraints, Ann. Oper. Res., 142 (2006), pp. 165-186.
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  • 8
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    • LOVEJOY, W.S.1
  • 9
    • 0000494894 scopus 로고
    • Computationally feasible bound for partially observed Markov decision processes
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  • 11
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.