Note on a Class of Admission Control Policies for the Stochastic Knapsack Problem
Part of the
Lecture Notes in Computer Science
book series (LNCS, volume 4041)
In this note we discuss a class of exponential penalty function policies recently proposed by Iyengar and Sigman for controlling a stochastic knapsack. These policies are based on the optimal solution of some related deterministic linear programs. By finding explicitly their optimal solution, we reinterpret the exponential penalty function policies and show that they belong to the class of threshold policies. This explains their good practical behavior, facilitates the comparison with the thinning policy, simplifies considerably their analysis and improves the bounds previously proposed.
KeywordsService Time Penalty Function Knapsack Problem Reward Rate Threshold Policy
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Iyengar, G., Sigman, K.: Exponential penalty function control of loss networks. The Annals of Applied Probability 14(4), 1698–1740 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
Halfin, S., Whitt, W.: Heavy-traffic limits for queues with many exponential servers. Operations research 29, 567–588 (1981)zbMATHCrossRefMathSciNetGoogle Scholar
Kelly, F.P.: Loss Networks. Annals of Applied Probability 1, 319–378 (1991)zbMATHCrossRefMathSciNetGoogle Scholar
Martello, S., Toth, P.: Knapsack Problems: Algorithms and Computer Implementations. Wiley, Chichester (1990)zbMATHGoogle Scholar
Ross, K.W.: Multiservice Loss Models for Broadband Telecommunication Networks. Springer, Heidelberg (1995)zbMATHGoogle Scholar
Wolff, R.W.: Stochastic Modeling and the Theory of Queues. Prentice-Hall, Englewood Cliffs (1989)zbMATHGoogle Scholar
© Springer-Verlag Berlin Heidelberg 2006