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STATIC STOCHASTIC KNAPSACK PROBLEMS

Published online by Cambridge University Press:  16 October 2015

Kai Chen  and
Sheldon M. Ross
Kai Chen
Affiliation:
Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA 90089, USA E-mails: kaic@usc.edu; smross@usc.edu
Sheldon M. Ross
Affiliation:
Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA 90089, USA E-mails: kaic@usc.edu; smross@usc.edu
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Abstract

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Two stochastic knapsack problem (SKP) models are considered: the static broken knapsack problem (BKP) and the SKP with simple recourse and penalty cost problem. For both models, we assume: the knapsack has a constant capacity; there are n types of items and each type has an infinite supply; a type i item has a deterministic reward v i and a random weight with known distribution F i . Both models have the same objective to maximize expected total return by finding the optimal combination of items, that is, quantities of items of each type to be put in knapsack. The difference between the two models is: if knapsack is broken when total weights of items put in knapsack exceed the knapsack's capacity, for the static BKP model, all existing rewards would be wiped out, while for the latter model, we could still keep the existing rewards in knapsack but have to pay a fixed penalty plus a variant cost proportional to the overcapacity amount. This paper also discusses the special case when knapsack has an exponentially distributed capacity.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 29 , Issue 4 , October 2015 , pp. 527 - 546
Copyright
Copyright © Cambridge University Press 2015 

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