Risk criteria in a stochastic knapsack problem

Mordechai I. Henig*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We consider an investor who wants to allocate funds among several projects. Each project is expected to yield a certain reward, and the objective is that a total reward will achieve a certain given amount, called the target. This problem is relatively easy to solve when rewards are deterministic, but may be hard in a more realistic setting when the rewards are stochastic and the investor wants to maximize the probability of attaining the target. We show that, by combining dynamic programming with a search procedure, the stochastic version of the problem can be solved relatively fast when rewards are normally distributed. The procedure is also useful for other risk criteria, which involve both the mean and the variance of the total reward.

Original languageEnglish
Pages (from-to)820-825
Number of pages6
JournalOperations Research
Issue number5
StatePublished - 1990


Dive into the research topics of 'Risk criteria in a stochastic knapsack problem'. Together they form a unique fingerprint.

Cite this