An adaptive stochastic knapsack problem

Kai Chen and Sheldon M. Ross

European Journal of Operational Research, 2014, vol. 239, issue 3, 625-635

Abstract: We consider a stochastic knapsack problem in which the event of overflow results in the problem ending with zero return. We assume that there are n types of items available where each type has infinite supply. An item has an exponentially distributed random weight with a known mean depending on its type and the item’s value is proportional to its weight with a given factor depending on the item’s type. We have to make a decision on each stage whether to stop, or continue to put an item of a selected type in the knapsack. An item’s weight is learned when placed to the knapsack. The objective of this problem is to find a policy that maximizes the expected total values. Using the framework of dynamic programming, the optimal policy is found when n=2 and a heuristic policy is suggested for n>2.

Keywords: Decision process; Dynamic programming; Stochastic knapsack (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:239:y:2014:i:3:p:625-635

DOI: 10.1016/j.ejor.2014.06.027

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