Alejandro Toriello

Assistant Professor
H. Milton Stewart School of Industrial and Systems Engineering
Georgia Institute of Technology
765 Ferst Drive NW
Atlanta, GA 30332

Office: Groseclose 427
atoriello at isye dot gatech dot edu

About me

I am an assistant professor in Industrial Engineering at Georgia Tech. I am interested in the theory and applications of supply chain and logistics models primarily involving transportation and inventory decisions, and in related optimization topics. The methodologies I use to study these problems include linear, mixed-integer and dynamic programming.

My CV. (Last updated November 6, 2014.)


Submitted or Under Review

  1. D. Blado*, W. Hu*, A. Toriello. Semi-Infinite Relaxations for the Dynamic Knapsack Problem with Stochastic Item Sizes. Submitted 2015.

    We propose and compare relaxations for the knapsack problem where item sizes are random and the decision maker can observe an item's realized size before choosing the next item.

  2. R. Fukasawa, A. Sapucaia Barboza, A. Toriello. A Comparison of Bounds for the Traveling Salesman Problem. Submitted 2015.

    We study and compare two recently proposed families of bounds for the TSP, one given by an approximate linear programming relaxation, and another stemming from branch-cut-and-price techniques.

    An earlier proof of Theorem 3 appeared in the working paper Equivalence of an Approximate Linear Programming Bound with the Held-Karp Bound for the Traveling Salesman Problem.

  3. M. Klapp*, A.L. Erera and A.Toriello. The One-Dimensional Dynamic Dispatch Waves Problem. Submitted 2015.

    Motivated by same-day delivery, we propose the dynamic dispatch waves problem to model the dynamics of a depot that receives orders throughout a service day and must fulfill them by dispatching a single vehicle. We study the one-dimensional case where the depot is at the end of a line, and develop an optimal a priori policy, dual bounds and several dynamic heuristcs.

  4. A. Toriello and N.A. Uhan. Dynamic Linear Programming Games with Risk-Averse Players. Submitted 2015.

    We propose dynamic linear programming games to model situations where uncertain costs must be shared over time by agents whose attitudes towards uncertainty are captured by coherent dynamic risk measures. Whereas cooperation is always possible when the agents are risk neutral, it proves much more difficult in the presence of risk aversion.

  5. L. Rademacher, A. Toriello and J.P. Vielma. On Packing and Covering Polyhedra in Infinite Dimensions. Submitted 2014.

    We study the natural extensions of packing and covering polyhedra to arbitrary dimensions and give sufficient conditions for complementary slackness and integrality of extreme points.

  6. W. Hu*, M.S. Lavieri, A. Toriello and X. Liu. Strategic Health Workforce Planning. Submitted 2014.

    We propose an infinite linear programming model for long-term workforce planning of a single worker type, e.g. nurses, in a large health care system. We give a series of conditions a system of this kind should satisfy, and use them to prove the optimality of a natural lookahead policy.

    Honorable Mention, INFORMS SPPSN Best Paper Award, 2013.

  7. J. Woodruff, W.B. Haskell and A. Toriello. Optimized Financial Systems Helps Customers Meet their Personal Finance Goals with Optimization. Submitted 2013.

    We explain how Optimized Financial Systems uses customers' financial information and actuarial data in an optimization model to give recommendations on investments and tax planning, particularly focused on individual retirement arrangements (IRAs).

Published or Accepted

  1. G.J. Schell, X. Li, M.S. Lavieri, A. Toriello, K.K. Martyn and G.L. Freed. Strategic Modeling of the Pediatric Nurse Practitioner Workforce: How Policy Changes Can Yield Self-Sufficiency. Pediatrics. 135:298-306, 2015.

    We assess the current U.S. pediatric nurse practitioner workforce and investigate the impact of potential policy changes to address forecasted shortages.

  2. A. Toriello, W.B. Haskell and M. Poremba*. A Dynamic Traveling Salesman Problem with Stochastic Arc Costs. Operations Research. 62:1107-1125, 2014.

    We propose a TSP with stochastic arc costs in which the salesman can observe outgoing arc costs at every city before choosing where to go next. We use approximate linear programming to tractably bound the problem and construct high-quality policies.

  3. C. Nguyen*, M. Dessouky and A. Toriello. Consolidation Strategies for the Delivery of Perishable Products. Transportation Research Part E: Logistics and Transportation Review. 69:108-121, 2014.

    We study an agricultural supply chain with stochastic demand for perishable goods, where several suppliers can save on transportation costs by consolidating shipments, and propose a simple look-ahead heuristic.

  4. A. Toriello. Optimal Toll Design: A Lower Bound Framework for the Asymmetric Traveling Salesman Problem. Mathematical Programming. 144:247-264, 2014.

    We propose a framework of lower bounds for the asymmetric TSP based on approximating the dynamic programming formulation. We then introduce an exact reformulation that generates a family of polynomially-solvable, successively tighter lower bounds. We show that the base member of this family yields a bound greater than or equal to the well-known Held-Karp bound.

  5. A. Toriello and N.A. Uhan. Dynamic Cost Allocation for Economic Lot Sizing Games. Operations Research Letters. 42:82-84, 2014.

    For lot sizing situations in which multiple retailers or producers can pool orders, we construct allocations dynamically over time so that costs are met as they are incurred and no one has the incentive to defect at any point.

  6. A. Toriello and N.A. Uhan. On Traveling Salesman Games with Asymmetric Costs. Operations Research, 61:1429-1434, 2013. (Technical note.)

    We consider cooperative traveling salesman games with non-negative asymmetric costs satisfying the triangle inequality. Using a variant of the Held-Karp relaxation and its dual, we construct a stable cost allocation with budget balance guarantee equal to the Held-Karp integrality gap for the asymmetric traveling salesman problem.

  7. C. Nguyen*, A. Toriello, M. Dessouky and J. Moore. Evaluation of Transportation Practices in the California Cut Flower Industry. Interfaces. 43:182-193, 2013.

    We evaluate the California cut flower industry’s current transportation practices and investigate the feasibility and cost of establishing a shipping consolidation center in Oxnard, California.

  8. D. Papageorgiou, A. Toriello, G. Nemhauser and M. Savelsbergh. Fixed-Charge Transportation with Product Blending. Transportation Science. 46:281-295, 2012.

    We introduce a fixed-charge transportation problem with linear product blending and give a polyhedral analysis. Applications include transportation problems in the petrochemical, energy and agriculture industries.

  9. A. Toriello and J.P. Vielma. Fitting a Continuous Piecewise Linear Function. European Journal of Operational Research. 219:86-95, 2012.

    We study models for piecewise linear data fitting (regression), including new mixed-binary models with variable regions. Applications include approximate inventory valuation.

  10. A. Toriello and G. Nemhauser. The Value Function of an Infinite-Horizon Single-Item Lot-Sizing Problem. Operations Research Letters. 40:12-14, 2012.

    We characterize the value function of a discounted, infinite-horizon variant of the single-item production lot-sizing problem and show that it inherits several structural properties from finite mixed-integer program value functions.

  11. A. Toriello, G. Nemhauser and M. Savelsbergh. Decomposing Inventory Routing Problems with Approximate Value Functions. Naval Research Logistics. 57:718-727, 2010.

    We introduce a time decomposition for inventory routing problems that depends on approximately valuing inventories at suppliers and consumers. Computational experiments use maritime inventory routing instances.

  12. F. Kılınç-Karzan, A. Toriello, S. Ahmed, G. Nemhauser and M. Savelsbergh. Approximating the Stability Region for Binary Mixed-Integer Programs. Operations Research Letters. 37:250-254, 2009.

    We develop an algorithm to calculate how stable a solution to a binary mixed-integer program is with respect to cost changes. Applications include real-time decision making scenarios, such as iterative combinatorial auctions.


  1. A. Toriello. Time Decomposition of Multi-Period Supply Chain Models. Ph.D. Thesis. Georgia Institute of Technology, December 2010.

  2. A. Toriello. A Brief Lecture on Submodular Functions.

* Indicates supervised student co-author.

Recent/Upcoming Presentations

Other Activities


ISyE 3103 - Supply Chain Modeling: Logistics

ISyE 3133 - Engineering Optimization

ISyE 4301 - Supply Chain Economics

ISyE 7203 - Logistics Systems Engineering

ISE 330 - Introduction to Operations Research: Deterministic Models (USC)

ISE 532 - Network Flows (USC)


Shabbir Ahmed, Christiane Barz, Maged Dessouky, Alan Erera, Ricardo Fukasawa, Will Haskell, Fatma Kılınç-Karzan, Mariel Lavieri, Jim Moore, George Nemhauser, Christine Nguyen, Dimitri Papageorgiou, Luis Rademacher, Martin Savelsbergh, Nelson Uhan, Juan Pablo Vielma, Joshua Woodruff.