Nikolaos Trichakis

Assistant Professor of Business Administration

Unit: Technology and Operations Management

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Nikos Trichakis is an assistant professor of business administration in the Technology and Operations Management Unit, teaching the Technology and Operations course in the MBA required curriculum and the Operations Management course in the doctoral curriculum.

In his research, Professor Trichakis investigates the interplay of fairness and efficiency in resource allocation problems and operations, together with the inherent tradeoffs that arise in balancing these objectives. He is interested in diverse industry applications ranging from health care to airlines to finance. His work has been published in Management Science and Operations Research.

Professor Trichakis received his Ph.D. in operations research from the Massachusetts Institute of Technology. He also holds MS degrees from Stanford University and Imperial College (UK), and a BS degree from Aristotle University (Greece), all in electrical and computer engineering. Before his doctoral studies, Professor Trichakis worked in software development at Sungard APT in London.

Featured Work

Publications

Journal Articles

  1. Pareto Efficiency in Robust Optimization

    This paper formalizes and adapts the well-known concept of Pareto efficiency in the context of the popular robust optimization (RO) methodology for linear optimization problems. We argue that the classical RO paradigm need not produce solutions that possess the associated property of Pareto optimality and illustrate via examples how this could lead to inefficiencies and sub-optimal performance in practice. We provide a basic theoretical characterization of Pareto robustly optimal (PRO) solutions, extend the RO framework by proposing practical methods that verify Pareto optimality, and generate solutions that are PRO. Critically important, our methodology involves solving optimization problems that are of the same complexity as the underlying robust problems, hence the potential improvements from our framework come at essentially limited extra computational cost. We perform numerical experiments drawn from three different application areas (portfolio optimization, inventory management, and project management), which demonstrate that PRO solutions have a significant potential upside compared with solutions obtained via classical RO methods.

    Keywords: robust optimization; Pareto optimality; Resource Allocation; Game Theory;

    Citation:

    Iancu, Dan, and Nikolaos Trichakis. "Pareto Efficiency in Robust Optimization." Management Science 60, no. 1 (January 2014): 130–147. View Details
  2. Fairness, Efficiency and Flexibility in Organ Allocation for Kidney Transplantation

    We propose a scalable, data-driven method for designing national policies for the allocation of deceased donor kidneys to patients on a waiting list, in a fair and efficient way. We focus on policies that have the same form as the one currently used in the United States. In particular, we consider policies that are based on a point system, which ranks patients according to some priority criteria, e.g., waiting time, medical urgency, etc., or a combination thereof. Rather than making specific assumptions about fairness principles or priority criteria, our method offers the designer the flexibility to select his desired criteria and fairness constraints from a broad class of allowable constraints. The method then designs a point system that is based on the selected priority criteria and approximately maximizes medical efficiency, i.e., life year gains from transplant, while simultaneously enforcing selected fairness constraints. Among the several case studies we present employing our method, one case study designs a point system that has the same form, uses the same criteria, and satisfies the same fairness constraints as the point system that was recently proposed by U.S. policymakers. In addition, the point system we design delivers an 8% increase in extra life year gains. We evaluate the performance of all policies under consideration using the same statistical and simulation tools and data as the U.S. policymakers use. Other case studies perform a sensitivity analysis (for instance, demonstrating that the increase in extra life year gains by relaxing certain fairness constraints can be as high as 30%) and also pursue the design of policies targeted specifically at remedying criticisms leveled at the recent point system proposed by U.S. policymakers.

    Keywords: fairness; health care policy; healthcare; Fairness; Resource Allocation; Policy; Health Care and Treatment; Medical Specialties; Health Industry; United States;

    Citation:

    Bertsimas, Dimitris, Vivek F. Farias, and Nikolaos Trichakis. "Fairness, Efficiency and Flexibility in Organ Allocation for Kidney Transplantation." Operations Research 61, no. 1 (January–February 2013): 73–87. View Details
  3. On the Efficiency-Fairness Trade-Off

    This paper deals with a basic issue: How does one approach the problem of designing the "right" objective for a given resource allocation problem? The notion of what is right can be fairly nebulous; we consider two issues that we see as key: efficiency and fairness. We approach the problem of designing objectives that account for the natural tension between efficiency and fairness in the context of a framework that captures a number of resource allocation problems of interest to managers. More precisely, we consider a rich family of objectives that have been well studied in the literature for their fairness properties. We deal with the problem of selecting the appropriate objective from this family. We characterize the trade-off achieved between efficiency and fairness as one selects different objectives, and we develop several concrete managerial prescriptions for the selection problem based on this trade-off. Finally, we demonstrate the value of our framework in a case study that considers air traffic management.

    Keywords: resource allocation; fairness; decision support; Cost vs Benefits; Fairness; Resource Allocation; Performance Efficiency; Air Transportation Industry;

    Citation:

    Bertsimas, Dimitris, Vivek F. Farias, and Nikolaos Trichakis. "On the Efficiency-Fairness Trade-Off." Management Science 58, no. 12 (December 2012): 2234–2250. View Details
  4. The Price of Fairness

    In this paper we study resource allocation problems that involve multiple self-interested parties or players and a central decision maker. We introduce and study the price of fairness, which is the relative system efficiency loss under a "fair" allocation assuming that a fully efficient allocation is one that maximizes the sum of player utilities. We focus on two well-accepted, axiomatically justified notions of fairness, viz., proportional fairness and max-min fairness. For these notions we provide a tight characterization of the price of fairness for a broad family of problems.

    Keywords: Price; Fairness;

    Citation:

    Bertsimas, Dimitris, Vivek F. Farias, and Nikolaos Trichakis. "The Price of Fairness." Operations Research 59, no. 1 (January–February 2011): 17–31. View Details

Cases and Teaching Materials

  1. Infection Control at Massachusetts General Hospital

    The case explores the challenges facing Massachusetts General Hospital concerning the adoption of a new infection control policy, which promises to improve operational performance, patient safety, and profitability. The new policy requires coordination between different departments within the hospital, namely the Emergency Department, the Infection Control Unit, and Admission Services. Students are initially asked to assess the operational, financial and clinical implications of the new policy. They are then asked to examine different approaches to its implementation.

    Objective: The case allows readers to examine a setting where internal coordination across different departments provides significant aggregate benefits for an organization. Coordination in this case, however, also leads to inequitable allocation of costs and benefits across the different departments, which then provides students with an opportunity to explore various implementation challenges and strategies.

    Keywords: Safety; Organizational Change and Adaptation; Integration; Health Care and Treatment; Policy; Health Industry; Boston;

    Citation:

    Huckman, Robert S., and Nikolaos Trichakis. "Infection Control at Massachusetts General Hospital." Harvard Business School Case 614-044, November 2013. View Details

    Research Summary

  1. Fairness and Efficiency in Resource Allocation

    In studying the relationship of fairness and efficiency, Professor Trichakis takes the novel approach of looking at varied industries for unifying factors, and he pays special attention to inequities by incorporating both quantitative work in social welfare and the philosophical literature on fairness. He has applied his model primarily to organ donation allocation and air traffic scheduling, asking whether the “natural” objective of efficiency is the right one.

    Organ donation allocation

    UNOS, the United Network for Organ Sharing, is revising its allocation policies, which determine how deceased-donor organs are offered to patients on a waiting list. Since a successful transplantation typically increases the life expectancy of the recipient, the natural objective for the UNOS might be to maximize the resulting aggregate life year gains. Yet a policy based on this efficiency rationale would fail to account for inequities to particular subsets of patients, based, for example, on their age or overall health status. Professor Trichakis has developed a points-based mechanism that takes fairness constraints as input and in a systematic way designs an allocation policy to maximize anticipated net life year gains while satisfying the fairness constraints. This mechanism has broad applicability to other dynamic allocation problems in health care and beyond.

    Air traffic scheduling

    The U.S. Federal Aviation Administration (FAA) needs to reallocate landing and take-off slots among the airlines in a way that minimizes system delay costs but also ensures that all gains from optimization are split among the airlines in an equitable fashion. Professor Trichakis has developed a concrete, quantitative statement of the design problem that might be solved as the FAA seeks the “right” operational objective. He also gauges the consequences of various solutions by using detailed historical air traffic data.

    Teaching

  1. George B. Dantzig Dissertation Award: Third Prize Winner of the 2012 George B. Dantzig Dissertation Award from the Institute for Operations Research and the Management Sciences (INFORMS).

  2. Pierskalla Award: Finalist for the 2011 Pierskalla Award from the Health Applications Society of the Institute for Operations Research and the Management Sciences (INFORMS) for his paper with Dimitris Bertsimas and Vivek F. Farias, "Fairness, Efficiency and Flexibility in Organ Allocation for Kidney Transplantation" (Operations Research, January–February 2013).