We consider a general online stochastic optimization problem with multiple budget
constraints over a horizon of finite time periods. In each time period, a reward function and …

We study the classical Network Revenue Management (NRM) problem with accept/reject
decisions and $ T $ IID arrivals. We consider a distributional form where each arrival must …

We consider the problem of online local false discovery rate (FDR) control where multiple
tests are conducted sequentially, with the goal of maximizing the total expected number of …

This paper studies the online stochastic resource allocation problem (RAP) with chance
constraints. The online RAP is a 0-1 integer linear programming problem where the …

This paper studies the online stochastic resource allocation problem (RAP) with chance
constraints and conditional expectation constraints. The online RAP is an integer linear …

We study a type of Online Linear Programming (OLP) problem that maximizes the objective
function with stochastic inputs. The performance of various algorithms that analyze this type …

We study how volume flexibility, when properly configured into production systems, can be
used to determine the optimal capacity level while satisfying designated performance …

This article is a survey of results concerning an inequality, which may be seen as a versatile
tool to solve problems in the domain of Applied Probability. The inequality, which we call …

We consider an online two-stage stochastic optimization with long-term constraints over a
finite horizon of $ T $ periods. At each period, we take the first-stage action, observe a model …

I use empirical processes to study how the shadow prices of a linear program that allocates
an endowment of n β∈ R m resources to n customers behave as n→∞. I show the shadow …