Conditions for the discovery of solution horizons

DOI10.1007/BF01581244zbMath0780.90107OpenAlexW2129212599MaRDI QIDQ2368078

Robert L. Smith, James C. Bean

Publication date: 22 August 1993

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01581244

zbMATH Keywords

dynamic programmingshortest pathundiscounted Markov decision processesoptimal searchdiscrete infinite horizon optimizationinfinite directed network

Mathematics Subject Classification ID

Programming involving graphs or networks (90C35) Markov and semi-Markov decision processes (90C40)

Related Items (8)

A stochastic programming approach for planning horizons of infinite horizon capacity planning problems ⋮ Infinite horizon programs; convergence of approximate solutions ⋮ Effective information for offline stochastic feedback and optimal control of dynamic systems ⋮ Solving infinite horizon optimization problems through analysis of a one-dimensional global optimization problem ⋮ Effective information horizon length in measuring off-line performance of stochastic dynamic systems ⋮ Solvability in infinite horizon optimization ⋮ A simplex algorithm for minimum-cost network-flow problems in infinite networks ⋮ A greedy algorithm for finding maximum spanning trees in infinite graphs

Cites Work

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• Turnpike Theory
• Technical Note—Identifying Forecast Horizons in Nonhomogeneous Markov Decision Processes
• A Finite Renewal Algorithm for the Knapsack and Turnpike Models
• Arbitrary State Markovian Decision Processes

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