Routing of airplanes to two runways: Monotonicity of optimal controls

Probability in the Engineering and Informational Sciences

Volumn 18, Issue 4, 2004, Pages 533-560

  Bauerle N ^a   Engelhardt Funke, O ^b   Kolonko, M ^b  

^a LEIBNIZ UNIVERSITY HANNOVER   (Germany)

^b CLAUSTHAL UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

AIRCRAFT; DECISION MAKING; GROUND OPERATIONS; RANDOM PROCESSES; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

DECISION MAKERS; LANDING OPERATIONS; OPTIMAL CONTROLS; OPTIMAL ROUTING; OPTIMAL STRATEGIES; QUEUING PROBLEMS; SEPARATION TIME; STOCHASTIC DYNAMIC PROGRAMMING;

DYNAMIC PROGRAMMING;

EID: 8744241413     PISSN: 02699648     EISSN: None     Source Type: Journal    
DOI: 10.1017/s0269964804184088     Document Type: Article

References (12)

1. Altman, E. & Stidham, S., Jr. (1995). Optimality of monotonic policies for two-action Markovian decision processes, with applications to control of queues with delayed information. Queueing Systems 21: 267-291.
2. Bäuerle, N., Engelhardt-Funke, O., & Kolonko, M. (2002). Routing of airplanes to two runways: Stability and bounds for the waiting times, submitted.
3. Beasley, J.E., Krishnamoorty, M., Sharaiha, Y.M., & Abramson, D. (2000). Scheduling aircraft landings - The static case. Transportation Science 34: 180-197.
4. Bertsekas, D. (1987). Dynamic programming: Deterministic and stochastic models. Englewood Cliffs, NJ: Prentice-Hall.
5. Bertsekas, D. & Tsitsiklis, J.N. (1996). Neuro-dynamic programming. Englewood Cliffs, NJ: Prentice-Hall.
6. Bolender, M.A. & Slater, G.L. (2000). Evaluation of scheduling methods for multiple runways. Journal of Aircrafts 37: 410-416.
7. Hordijk, A., Koole, G.M., & Loeve, J.A. (1994). Analysis of a customer assignment model with no state information. Probability in the Engineering and Information Sciences 8: 419-429.
8. Horonjeff, R. & McKelvey, F.X. (1994). Planning and design of airports, 4th ed. Boston: McGraw-Hill.
9. Neuts, M.F. (1977). Some explicit formulas for the steady-state behaviour of the queue with semi-Markovian service times. Advances in Applied Probability 9: 141-157.
10. Puterman, M.L. (1994). Markov decision processes. Discrete stochastic dynamic programming. Wiley Series in Probability and Mathematical Statistics. New York: Wiley.
11. Schäl, M. (1975). Conditions for the optimality in dynamic programming and for the limit of n-stage optimal policies to be optimal. Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete, 32: 179-196.
12. Stidham, S., Jr. & Weber, R. (1993). A survey of Markov decision models for control of networks of queues. Queueing Systems 13: 291-314.