About

Sunil Chopra is the IBM Distinguished Professor of Operations Management at the Kellogg School of Management, Northwestern University. He has served as Interim Dean of the Kellogg School of Management from 2009 to 2010 and was the Senior Associate Dean for Curriculum and Teaching from 2006 to 2009. Professor Chopra joined the Kellogg faculty in 1989 and previously held an Assistant Professor position at the Stern School of Business Administration at New York University. He holds a PhD in Operations Research from SUNY Stony Brook. His research and teaching interests are in Operations Management, Logistics and Distribution Management, design of communication networks, and design of distribution networks. He has co-authored books on Managing Business Process Flows and Supply Chain Management: Strategy, Planning, and Operation, which are used in top business schools and have received awards such as the best book of the year in 2002 by the Institute of Industrial Engineers. Professor Chopra has received several teaching awards at Kellogg and has held editorial positions in prominent journals including Management Science and Operations Research. His recent research focuses on risk management in supply chains and analyzing distribution systems to identify market, manufacturing, and product characteristics that influence supply chain structure. He has also consulted for various firms in his areas of expertise.

Research topics

• Computer Science
• Economics
• Marketing
• Business
• Mathematics
• Computer network
• Environmental economics
• Mathematical optimization
• Transport engineering
• Engineering
• Industrial organization
• Operations research
• Operations management

Selected publications

• 0707 Efficacy of ChatGPT-4o in recognizing and diagnosing skin cancer subtypes in light-skin and skin-of-color based on high-quality clinical images

  Journal of Investigative Dermatology · 2025-07-21

  article1st authorCorresponding
  PublisherDOI

• The Role of Oral Isotretinoin in Thick Skin Rhinoplasty: A Systematic Review

  Facial Plastic Surgery · 2025-09-08

  review

  Thick skin poses a challenge in rhinoplasty, often resulting in an undefined tip and supratip deformities.This study evaluates oral isotretinoin as an adjuvant treatment for thick-skinned rhinoplasty patients.This is a systematic review conducted in accordance with PRISMA guidelines.Two independent investigators performed a comprehensive literature search to identify studies that assessed perioperative oral isotretinoin treatment in thick skin rhinoplasty patients. Key outcome measures include skin thickness reduction, cosmetic surgical outcomes, and postoperative patient satisfaction.Five studies met the study inclusion criteria. Their findings demonstrated that oral isotretinoin effectively reduces skin thickness and improves cosmetic outcomes and satisfaction up to 6 months postoperatively, with no major complications reported.Although evidence is limited, oral isotretinoin shows promise in enhancing short-term rhinoplasty outcomes for thick-skinned patients. Further, high-quality trials are needed to confirm these results and develop standardized treatment protocols.

  PublisherDOI

• Fast-food stores with a drive-through recovered post-pandemic; Stores without did not

  SSRN Electronic Journal · 2024-01-01

  articleOpen access
  PublisherDOI

• Using anticipatory orders to manage disruption risk over a short product life cycle

  European Journal of Operational Research · 2024-06-10 · 6 citations

  article1st author
  PublisherDOI

• Dual-sourcing of capacity

  SSRN Electronic Journal · 2023-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• The Value of Information and Flexibility with Temporal Commitments

  Manufacturing & Service Operations Management · 2022-03-18 · 3 citations

  article

  Problem definition: We study the combined value of observing future demand realizations (partial demand visibility) and flexible capacity, two hedging mechanisms against demand uncertainty, when signing capacity contracts with short temporal commitment. Academic/practical relevance: With new technological innovations, short commitment contracts are found in dynamic environments like distribution, processing, and manufacturing, a trend likely to grow in the future. In contrast to classic procurement, where commitments are long, short commitments lead to new dynamics in which demand visibility allows companies to use flexible resources more efficiently by adapting to demand observations. Methodology: We incorporate flexible capacity and demand visibility simultaneously using a multiperiod newsvendor network model with two nodes that are supplied using dedicated and flexible capacity contracts with short temporal commitment. Results: The optimal commitment to capacity contracts adapts within bounds to the observed demand at each node. The ability to adapt to visible demand becomes more valuable when flexible capacity contracts are available. This allows us to show that demand visibility and flexible capacity can act as complements. Managerial implications: In contrast to conventional wisdom, when contracts have short commitment, companies can enhance the value of demand visibility if flexible capacity is also available as an option.

  PublisherDOI

• Extended Graph Formulation for the Inequity Aversion Pricing Problem on Social Networks

  INFORMS journal on computing · 2022-02-02 · 2 citations

  article1st authorCorresponding

  The inequity aversion pricing problem aims to maximize revenue while providing prices to people connected in a social network such that connected people receive prices that are not too different. This problem is known to be NP-hard even when the number of prices offered is three. This paper provides an extended graph formulation for the problem whose LP-relaxation is shown to be very strong. We show that the extended graph relaxation is integral on a network without any cycle. We develop extended cycle inequalities and show that the extended cycle inequalities cut off all the fractional extreme points of the extended graph relaxation on a cycle. We generalize cycle inequalities to zero half cuts performing a Chvátal–Gomory procedure on a cycle. Computational experiments show that the extended graph relaxation results in an integer solution for most problem instances with very small gaps (less than 3%) from optimality for the remaining instances. The addition of zero half cuts reduces the integrality gap significantly on the few difficult instances. Summary of Contribution: The inequity aversion pricing problem aims to maximize revenue while providing prices to people connected in a social network such that connected people receive prices that are not too different. This paper provides an extended graph formulation of this practical revenue management problem whose LP-relaxation is shown to be very strong. The authors show that the extended graph relaxation is integral on a network without any cycle. They develop extended cycle inequalities and generalize them to zero-half cuts. Computational experiments show that the extended graph formulation results in an integer solution or a very small integrality gap. For difficult instances, the addition of zero half cuts significantly reduces the integrality gap.

  PublisherDOI

• A Bounded Formulation for The School Bus Scheduling Problem

  Transportation Science · 2022 · 18 citations

  • Computer Science
  • Mathematical optimization
  • Computer Science

  This paper proposes a new formulation for the school bus scheduling problem (SBSP), which optimizes school start times and bus operation times to minimize transportation cost. The goal is to minimize the number of buses to serve all bus routes such that each route arrives in a time window before school starts. We show that introducing context-specific features, common in many school districts, can lead to a new time-indexed integer linear programming (ILP) formulation. Based on a strengthened version of the linear relaxation of the ILP, we develop a dependent randomized rounding algorithm that yields near-optimal solutions for large-scale problem instances. The efficient formulation and solution approach enable quick generation of multiple solutions to facilitate strategic planning, which we demonstrate with data from two public school districts in the United States. We also generalize our methodologies to solve a robust version of the SBSP.

  PublisherDOI

• An Exact Solution Method for the Political Districting Problem

  Parallel Processing Letters · 2022-10-28

  article1st author

  Mehrotra, Johnson, and Nemhauser (1998) [Management Science 44, pp. 1100–1114] addressed a problem for political districting and developed an optimization based heuristic to find good districting plans which partition the population units into contiguous districts with equal populations. Their case study found a good South Carolina plan at a penalty cost of 68. This paper develops a strong integer programming model identifying the exact optimal solution. Our model identifies the optimal South Carolina plan at the minimum penalty of 64. Motivated by the 2019 lawsuit challenging the congressional plan as gerrymandering, we inspect the actual Maryland plan.

  PublisherDOI

• Parallel Power System Restoration

  arXiv (Cornell University) · 2022-04-04

  preprintOpen access1st authorCorresponding

  Power system restoration is an essential activity for grid resilience, where grid operators restart generators, re-establish transmission paths, and restore loads after a blackout event. With a goal of restoring electric service in the shortest time, the core decisions in restoration planning are to partition the grid into sub-networks, each of which has an initial power source for black-start (called sectionalization problem), and then restart all generators in each network (called generator startup sequencing problem or GSS) as soon as possible. Due to the complexity of each problem, the sectionalization and GSS problems are usually solved separately, often resulting in a sub-optimal solution. Our paper develops models and computational methods to solve the two problems simultaneously. We first study the computational complexity of the GSS problem and develop an efficient integer linear programming formulation. We then integrate the GSS problem with the sectionalization problem and develop an integer linear programming formulation for the parallel power system restoration (PPSR) problem to find exact optimal solutions. To solve larger systems, we then develop bounding approaches that find good upper and lower bounds efficiently. Finally, to address computational challenges for very large power grids, we develop a randomized approach to find a high-quality feasible solution quickly. Our computational experiments demonstrate that the proposed approaches are able to find good solutions for PPSR in up to 2000-bus systems.

  PublisherOA PDFDOI

Frequent coauthors

• ManMohan S. Sodhi

  12 shared

• Sangho Shim

  Robert Morris University

  12 shared

• M. R. Rao

  11 shared

• Achal Bassamboo

  10 shared

• Karen Smilowitz

  10 shared

• Florian Lücker

  9 shared

• Peter Meindl

  Wake Forest University

  8 shared

• Mark S. Daskin

  7 shared

Awards & honors

• Saul Gass Expository Writing Award, INFORMS Annual Meeting,…
• Winner Case Category - Indian Management issues and Opportun…
• Kellogg Alumni Professor of the Year Award, Kellogg School o…
• Selected IIE Book of the Year for Supply Chain Management, I…
• Executive MBA Program Outstanding Teaching Awards, Kellogg S…