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We consider online versions of the Traveling Salesman Problem (TSP) and Traveling Repairman Problem (TRP) where instances are not known in advance. Cities (points) to be visited are revealed over time, while the server is en route serving previously released requests. These problems are known in the literature as the Online TSP (TRP, respectively). The(More)
We consider online routing optimization problems where the objective is to minimize the time needed to visit a set of locations under various constraints; the problems are online because the set of locations are revealed incrementally over time. We consider two main problems: (1) the online Traveling Salesman Problem (TSP) with precedence and capacity(More)
In this paper we consider a location-optimization problem where the classical unca-pacitated facility location model is recast in a stochastic environment with several risk factors that make demand at each customer site probabilistic and correlated with demands at the other customer sites. Our primary contribution is to introduce a new solution methodology(More)
We consider the problem min x∈{0,1} n {c x : a j x ≤ bj, j = 1,. .. , m}, where the aj are random vectors with unknown distributions. The only information we are given regarding the random vectors aj are their moments, up to order k. We give a robust formulation, as a function of k, for the 0-1 integer linear program under this limited distributional(More)
We study inventory management problems where demands are revealed incrementally and procurement decisions must be made before the demands are realized. There are no probabilistic distributions nor non-trivial bounds to characterize demands. We consider two cost minimization problems: (1) perishable products with lost sales and (2) durable products with(More)