Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hypergraphs, certain… (More)

Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hypergraphs, certain… (More)

We study the distance constrained vehicle routing problem (DVRP) (Laporte et al., Networks 14 (1984), 47–61, Li et al., Oper Res 40 (1992), 790–799): given a set of vertices in a metric space, a… (More)

Consider a random graph model where each possible edge e is present independently with some probability p e . Given these probabilities, we want to build a large/heavy matching in the randomly… (More)

In the Stochastic Orienteering problem, we are given a metric, where each node also has a job located there with some deterministic reward and a random size. (Think of the jobs as being chores one… (More)

We study a general stochastic probing problem defined on a universe V , where each element e ∈ V is “active” independently with probability pe. Elements have weights {we : e ∈ V } and the goal is to… (More)

We study the <i>k</i>-multicut problem: Given an edge-weighted undirected graph, a set of <i>l</i> pairs of vertices, and a target <i>k</i> ≤ <i>l</i>, find the minimum cost set of edges whose… (More)

We study a basic resource allocation problem that arises in cloud computing environments. The physical network of the cloud is represented as a graph with vertices denoting servers and edges… (More)

In the classical k-median problem, we are given a metric space and would like to open k centers so as to minimize the sum (over all the vertices) of the distance of each vertex to its nearest open… (More)