Combinatorial Optimization Reading Group - David Aleman
Title: Approximation Algorithms for Stochastic Knapsack
Speaker: | David Aleman |
Affiliation: | University of Waterloo |
Location: | MC 6029 or contact Rian Ne |
Abstract: The classical Knapsack problem takes as input a set of items with some fixed nonnegative values and weights. The goal is to compute a subset of items of maximum total value, subject to the constraint that the total weight of these elements is at most a given limit. In this talk we review a paper by Gupta, Krishnaswamy, Molinaro and Ravi, in which the following stochastic variation of this problem is considered: the value and weight of each item are correlated random variables with known, arbitrary distributions.