Contributors

Abstract

Elodie Adida (“ Supply Chain Competition with Multiple Manufacturers and Retailers ”) is assistant professor of industrial engineering at the University of Illinois at Chicago. Her research interest is on the modeling and solution of optimization problems in a variety of areas, in particular those involving game theory. Her recent work includes disaster planning, influenza vaccine supply chain, pricing, and inventory management. Edoardo Amaldi (“ Solving Nonlinear Covering Problems Arising in WLAN Design ”) received the “Diplome” in mathematical engineering and the “Doctorat ès Sciences” (Ph.D.) from the Swiss Federal Institute of Technology at Lausanne (EPFL). From 1995 to 1998 he was a research associate at the School of Operations Research and Industrial Engineering, Cornell University. Since 1999 he has been with the Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy, where he is an associate professor in operations research. His main research interests are in discrete optimization and in the design and analysis of algorithms, with applications in telecommunications, data mining, transportation, health-care management, and image processing. Mor Armony (“ Routing and Staffing in Large-Scale Service Systems: The Case of Homogeneous Impatient Customers and Heterogeneous Servers ”) is an associate professor of operations management at the Stern School of Business at New York University. Her research focuses on large-scale service operations. Particularly, she studies issues related to staffing and skill-based routing in customer contact centers and managing patient flow in hospitals. Balabhaskar Balasundaram (“ Clique Relaxations in Social Network Analysis: The Maximum k-Plex Problem ”) is an assistant professor in the School of Industrial Engineering and Management at Oklahoma State University. He received his Ph.D. in industrial engineering from Texas A&M University in 2007 and his B.Tech. in mechanical engineering from the Indian Institute of Technology–Madras in 2002. His research interests are in the theoretical, algorithmic, and computational aspects of combinatorial optimization problems. His current focus is on discrete and continuous optimization methods to solve combinatorial optimization problems that arise in graph-based data mining and clustering of social, biological, and wireless networks. He also takes a keen interest in optimization under uncertainty, graph theory, and complexity theory. Roberto Baldacci (“ An Exact Algorithm for the Period Routing Problem ”) is a researcher in operations research at the Department of Electronics, Computer Science and Systems (DEIS) of the University of Bologna, Italy. His major research interests are in the areas of transportation planning, logistics and distribution, and the solution of vehicle routing and scheduling problems over street networks. His research activities are in the theory and in the applications of mathematical programming. He has worked in the design of new heuristic and exact methods for solving combinatorial problems as routing and location problems. Enrico Bartolini (“ An Exact Algorithm for the Period Routing Problem ”) is a post doc at the University of Bologna. His research activity concerns the study and development of heuristic and exact algorithms for solving combinatorial optimization problems with applications in logistics and distribution systems, in particular network design problems and some generalizations of the vehicle routing problem. Peter Berling (“ Optimal Inventory Policies when Purchase Price and Demand Are Stochastic ”) currently shares his time between the Engineering School at Lund University and the Business School at Linnaeus University. He also sits on the management team of the Swedish National Excellence Centre in logistics (NGIL). His research interest is in the broad field of supply chain management and optimal inventory control under price variation with stochastic demand. Dimitris Bertsimas (“ The Price of Fairness ” and “ An Integer Optimization Approach to Large-Scale Air Traffic Flow Management ”) is the Boeing Professor of Operations Research at the Massachusetts Institute of Technology, the codirector of the Operations Research Center at MIT, and a member of the National Academy of Engineering. His research interests include discrete, robust, and stochastic optimization and their applications. His first paper in this issue is part of the author's research in the context of resource allocation. His second paper in the issue is part of a broader investigation on models for air-traffic flow management that started in the mid-1990s. Omar Besbes (“ On the Minimax Complexity of Pricing in a Changing Environment ”) is an assistant professor of decision, risk, and operations at the Graduate School of Business, Columbia University. His research interests include dynamic pricing, revenue management, and service operations, with a particular emphasis on data-driven decision making. Sandro Bosio (“ Solving Nonlinear Covering Problems Arising in WLAN Design ”) received his M.S. in computer science from the Università degli Studi di Milano in 2002 and his Ph.D. in mathematical engineering from the Politecnico di Milano in 2006. Between January 2008 and August 2010 he was a researcher at the Otto-von-Guericke University of Magdeburg, Germany, and since September 2010 he has worked as a researcher at ETH Zürich. His current research activities are in integer programming, combinatorial optimization, complexity, and approximation theory. Sergiy Butenko (“ Clique Relaxations in Social Network Analysis: The Maximum k-Plex Problem ”) is an associate professor in the Department of Industrial and Systems Engineering at Texas A&M University. He holds B.S. and M.S. degrees in mathematics from Kyiv National Taras Shevchenko University and M.S. and Ph.D. in operations research from the University of Florida. His research interests are in global and discrete optimization with applications in network-based data mining, analysis of biological and social networks, wireless ad hoc and sensor networks, and energy. Binyuan Chen (“ Finite Disjunctive Programming Characterizations for General Mixed-Integer Linear Programs ”) is a Ph.D. student in the Systems and Industrial Engineering Department at the University of Arizona. His research is in parametric integer programming and its applications in power system operations. Jie Chen (“ Exact Analysis of a Lost Sales Model Under Stuttering Poisson Demand ”) is a Ph.D. candidate in the School of Operations Research and Information Engineering, Cornell University. She received a B.A. in applied probability and statistics from Peking University in 2005. Her research interests are inventory control, supply chain management, stochastic modeling, and simulations. Mark S. Daskin (“ The Adaptive Knapsack Problem with Stochastic Rewards ”) is the Clyde W. Johnson Collegiate Professor and Chair of the Department of Industrial and Operations Engineering at the University of Michigan. His research interests are in the application of operations research techniques to supply chain design and management problems with an emphasis on facility location modeling. He is also studying a number of health-care topics. Victor DeMiguel (“ Supply Chain Competition with Multiple Manufacturers and Retailers ”) is associate professor of management science and operations at the London Business School. His research focuses on the design, analysis, and application of optimization models and methods for managerial decision making. Applications include portfolio selection, equilibrium modeling and computation, and decomposition methods for stochastic and large-scale optimization. Vivek F. Farias (“ The Price of Fairness ”) is the Robert N. Noyce Career Development Assistant Professor of Management at the Sloan School of Management and the Operations Research Center at Massachusetts Institute of Technology. He works on revenue management, dynamic optimization, and the analysis of complex stochastic systems. The paper in this issue is part of the author's research in the context of resource allocation. Kay Giesecke (“ Risk Analysis of Collateralized Debt Obligations ”) is assistant professor of management science and engineering at Stanford University. His research and teaching interests are in the area of financial engineering. Illya V. Hicks (“ Clique Relaxations in Social Network Analysis: The Maximum k-Plex Problem ”) received a B.S. in mathematics from Southwest Texas State University (currently named Texas State University at San Marcos) in 1995. He received his M.A. and Ph.D. in computational and applied mathematics from Rice University, where he serves as an associate professor. His research interests are in combinatorial optimization, graph theory, and integer programming. Some applications of interest are network design, biological networks, cancer treatment, and logistics. His current research is focused on using graph decomposition techniques to solve computationally hard problems. L. Jeff Hong (“ Kernel Estimation of the Greeks for Options with Discontinuous Payoffs ”) is an associate professor of industrial engineering and logistics management at the Hong Kong University of Science and Technology. His research has focused on stochastic simulation and stochastic optimization, with applications in financial risk management, environmental policies, and logistics and supply chain management. Woonghee Tim Huh (“ Average Cost Single-Stage Inventory Models: An Analysis Using a Vanishing Discount Approach ”) is an assistant professor of operations and logistics in the Sauder School of Business at the University of British Columbia (UBC). His current research interests include developing data-driven adaptive policies and proving structural results in inventory theory. Prior to joining UBC, he was an associate professor in the Department of Industrial Engineering and Operations Research at Columbia University. He has received Columbia Engineering School's Distinguished Teaching Award and the Diversity Teaching Award. He received a B.A. in sociology, B.Math. in computer science, and M.Math. in combinatorics and optimization from the University of Waterloo. He holds an M.Sc. and a Ph.D. in operations research from Cornell University. Taylan İlhan (“ The Adaptive Knapsack Problem with Stochastic Rewards ”) received his Ph.D. from the Department of Industrial Engineering and Management Sciences of Northwestern University in 2007. He earned his B.S. and M.S. degrees in industrial engineering from Bilkent University, Ankara, Turkey and was awarded the Walter P. Murphy Fellowship by Northwestern University for graduate study in 2002. His research interests are stochastic modeling and optimization. He currently works at Quantlab Financial LLC as a quantitative researcher. Seyed M. R. Iravani (“ The Adaptive Knapsack Problem with Stochastic Rewards ”) is associate professor in the Department of Industrial Engineering and Management Sciences, Northwestern University. His research interests are in the applications of stochastic processes, game theory, and queuing theory to the design and control of manufacturing, service operations systems and supply chains, focusing on improving their flexibility, coordination, and responsiveness. Peter L. Jackson (“ Exact Analysis of a Lost Sales Model Under Stuttering Poisson Demand ”) is a professor in the School of Operations Research and Information Engineering, Cornell University, and was Director of the Cornell Systems Engineering Program (2003–2009). He holds degrees in economics (B.A., 1975, University of Western Ontario), statistics (M.Sc., 1978, Stanford University), and operations research (Ph.D., 1980, Stanford University). His research interests include manufacturing systems design and supply chain management. He has published articles in Operations Research, Mathematics of Operations Research, IIE Transactions, Management Science, and other publications. He is the recent author of a text used to introduce systems engineering to a nontechnical audience. Ganesh Janakiraman (“ Average Cost Single-Stage Inventory Models: An Analysis Using a Vanishing Discount Approach ”) is an associate professor of operations management at the School of Management in the University of Texas at Dallas. He obtained his B.Tech. degree in mechanical engineering from the Indian Institute of Technology–Madras and his M.S. and Ph.D. degrees in operations research from Cornell University. Prior to joining the University of Texas, he was an assistant professor at New York University's Stern School of Business. His research interests are broadly in the area of supply chain management with a special emphasis on inventory theory. An underlying theme of his research in inventory theory is mathematical analysis that directly or indirectly aids in the development of optimal or near-optimal algorithms to determine inventory levels in supply chains. Houyuan Jiang (“ Robust Newsvendor Competition Under Asymmetric Information ”) is a university senior lecturer in the Judge Business School at University of Cambridge. His research interests include revenue management, health-care operations, resource allocation, and optimization. Baeho Kim (“ Risk Analysis of Collateralized Debt Obligations ”) is assistant professor of finance at the Korea University Business School. His research and teaching interests are in the area of financial engineering. Simge Küçükyavuz (“ Finite Disjunctive Programming Characterizations for General Mixed-Integer Linear Programs ”) is an assistant professor in the Integrated Systems Engineering Department at the Ohio State University. Her research interests are in mixed-integer programming and its applications. She received her M.S. and Ph.D. from the University of California, Berkeley and her B.S. from the Middle East Technical University. Guangwu Liu (“ Kernel Estimation of the Greeks for Options with Discontinuous Payoffs ”) is an assistant professor in the Department of Management Sciences at City University of Hong Kong. His research interests include stochastic simulation and financial risk management. Guglielmo Lulli (“ An Integer Optimization Approach to Large-Scale Air Traffic Flow Management ”) is assistant professor of operations research at University of Milano–Bicocca. In 2007 he was recipient of a Fulbright Fellowship at the Massachusetts Institute of Technology. His research interests focus on deterministic and stochastic optimization particularly applied to transportation and logistics operations, air traffic flow management, and bio-computational problems. Federico Malucelli (“ Solving Nonlinear Covering Problems Arising in WLAN Design ”) received his Ph.D. in computer science in 1993. Since 2002 he has been full professor of operations research at the Politecnico di Milano. His main research interests include models and algorithms for combinatorial optimization problems, with applications in particular to telecommunications, transportation, logistics, and electronic circuit design. He has published more than 30 articles in international scientific journals. Avishai Mandelbaum (“ Routing and Staffing in Large-Scale Service Systems: The Case of Homogeneous Impatient Customers and Heterogeneous Servers ”) is the Benjamin & Florence Free Professor of Operations Research, Statistics and Service Engineering, at the Technion in Israel. His research is in the area of stochastic processes. Through research and teaching, he has been attempting to specialize and generalize the theory of queues to service systems, mainly telephone call centers and hospitals. The present paper is part of ongoing research on modeling and analyzing the trade-offs between efficiency and quality for systems that operate with many servers in heavy traffic. Victor Martínez-de-Albéniz (“ Optimal Inventory Policies when Purchase Price and Demand Are Stochastic ”) is assistant professor in IESE's Department of Production, Technology and Operations Management. His research focuses on understanding how supply chain decisions can help companies compete in the global arena. He is particularly interested in procurement, where models for supply base size, capacity and inventory management can be especially useful. Naomi Miller (“ Risk-Averse Two-Stage Stochastic Linear Programming: Modeling and Decomposition ”) has a mathematics degree from the University of Toronto and Ph.D. in operations research from Rutgers University. Her research interests are in the area of stochastic programming and applications of risk theory in finance. Currently she is working on an application of risk-based portfolio optimization to problems in the insurance industry. Aristide Mingozzi (“ An Exact Algorithm for the Period Routing Problem ”) is a professor of operations research at the Department of Mathematics of the University of Bologna, Italy. His main interests include mathematical programming, combinatorial optimization, graph theory, dynamic programming, and the development of exact and heuristic algorithms for the solution of real-life problems in distribution and scheduling. John A. Muckstadt (“ Exact Analysis of a Lost Sales Model Under Stuttering Poisson Demand ”) is Stephen H. Weiss Presidential Fellow and the Acheson/Laibe Professor of Business Management and Leadership Studies in the School of Operations Research and Information Engineering at Cornell University. He conducts research and teaches courses in manufacturing, supply chain, and inventory management. He is studying a number of issues related to control of service parts inventories. He is currently studying public health supply chain problem and is a member of the Board of Scientific Counselors of the Center for Disease Control and Prevention. Mahesh Nagarajan (“ Average Cost Single-Stage Inventory Models: An Analysis Using a Vanishing Discount Approach ”) is an assistant professor at the Sauder School of Business at the University of British Columbia. He obtained his Ph.D. from the Marshall School of Business at the University of Southern California, Los Angeles. Serguei Netessine (“ Robust Newsvendor Competition Under Asymmetric Information ”) is an associate professor of operations and information management at the Wharton School, University of Pennsylvania. His research focuses on the role of decentralized decision making and incentives in operational decisions, as well as on empirical studies of operational performance. This paper was written during his visit at INSEAD in Fontainebleau, France as a part of the Wharton–INSEAD Alliance. Amedeo Odoni (“ An Integer Optimization Approach to Large-Scale Air Traffic Flow Management ”) is professor of aeronautics and astronautics, professor of civil and environmental engineering, and a codirector of the Airline Industry Program at Massachusetts Institute of Technology (MIT). He has also served as codirector of the FAA's National Center of Excellence in Aviation Education, codirector of the Operations Research Center at MIT, editor of Transportation Science, and consultant to numerous international airport- and aviation-related organizations. His recent books include the bestselling textbook Airport Systems: Planning, Design and Management (McGraw-Hill 2003) coauthored with Richard de Neufville, and The Global Airline Industry (John Wiley 2009) coedited with Peter Belobaba and Cynthia Barnhart. Warren B. Powell (“ Information Collection on a Graph ”) is a professor in the Department of Operations Research and Financial Engineering at Princeton University, and director of CASTLE Laboratory. He has coauthored over 100 refereed publications in stochastic optimization, stochastic resource allocation, and related applications. He is the author of the book Approximate Dynamic Programming: Solving the Curses of Dimensionality, published by John Wiley & Sons. Currently he is involved in applications in energy, transportation, finance, and homeland security. Andrzej Ruszczyński (“ Risk-Averse Two-Stage Stochastic Linear Programming: Modeling and Decomposition ”) received his Ph.D. degree from Warsaw University of Technology (Poland). He has been with the University of Zurich (Switzerland), International Institute of Applied Systems Analysis (Austria), Princeton University, and the University of Wisconsin–Madison. He is currently with the Rutgers Business School, Rutgers University, New Jersey. His research interests are in the area of stochastic programming, and in particular risk-averse optimization, on which he published numerous articles. He is the author of recently published books Nonlinear Optimization (2006) and Stochastic Programming: Modeling and Theory (2009, with D. Dentcheva and A. Shapiro). Ilya O. Ryzhov (“ Information Collection on a Graph ”) is a Ph.D. candidate in the Department of Operations Research and Financial Engineering at Princeton University. He received a B.S. degree in computer science and an M.Eng. degree in operations research and industrial engineering from Cornell University, as well as an M.Sc. degree in management science from Stanford University. His Ph.D. dissertation deals with finding efficient algorithms for optimal learning in different classes of stochastic optimization problems, including graph problems, linear programs, and Markov decision processes. Sergei Savin (“ Robust Newsvendor Competition Under Asymmetric Information ”) is an associate professor of operations and information management at the Wharton School, University of Pennsylvania. His research interests include diagnostic and service capacity management in health-care operations, revenue management, and diffusion models for new products and services. Alan Scheller-Wolf (“ Scheduling of Dynamic In-Game Advertising ”) teaches in the operations management area at the Tepper School of Business of Carnegie Mellon University. His research focuses on stochastic processes and how they can be used to estimate and improve the performance of computer, communication, manufacturing and service systems, inventory systems, and supply chains. Suvrajeet Sen (“ Finite Disjunctive Programming Characterizations for General Mixed-Integer Linear Programs ”) is professor of industrial and systems engineering and director of the Center for Energy, Sustainability, and the Environment at the Ohio State University (OSU). Prior to joining OSU, he served on the faculty at the University of Arizona, and he also served as a program director at NSF where he was responsible for the operations research program and the service enterprise engineering program. His research is devoted to the theory and applications of large-scale optimization algorithms, especially those arising in stochastic programming. His applications contributions are mainly in infrastructure systems, including work on telecommunications network planning, traffic control in vehicular networks, and power generation networks. He has served on the editorial board of Operations Research for many years, including a stint as the area editor for optimization. Professor Sen is a Fellow of INFORMS. Ian H. Sloan (“ Quasi-Monte Carlo Methods in Financial Engineering: An Equivalence Principle and Dimension Reduction ”) is a Scientia professor at the School of Mathematics and Statistics of the University of New South Wales, Australia. He is also the Chair Professor at Hong Kong Polytechnic University under the Distinguished Scholars Scheme. He was elected a Fellow of the Australian Academy of Science in 1993. His research interests are in boundary integral methods, finite element methods, high-dimensional integration and approximation, information-based complexity, and the numerical analysis of integral and partial differential equations. Sridhar Tayur (“ Scheduling of Dynamic In-Game Advertising ”) is the Ford Distinguished Research Professor at the Tepper School of Business, and the Founder and CEO of SmartOps Corporation. He enjoys working on practical problems and implementing improved solutions collaboratively with industry or nonprofit organizations, especially when a new business model becomes available. Nikolaos Trichakis (“ The Price of Fairness ”) is a doctoral candidate at the Operations Research Center at Massachusetts Institute of Technology (MIT). His research interests lie in the fields of optimization, applied probability, and their applications, particularly in health care and finance. The paper in this issue is part of his Ph.D. thesis at MIT. John Turner (“ Scheduling of Dynamic In-Game Advertising ”) completed his Ph.D. in operations research at the Tepper School of Business, Carnegie Mellon University, and joined the Operations and Decision Technologies faculty at the Paul Merage School of Business, University of California, Irvine. His research applies operations research techniques to plan and price a wide variety of online advertising, including ads on Web pages, in video games, on electronic billboards, and in the next generation of digital TV. Andrea Valletta (“ An Exact Algorithm for the Period Routing Problem ”) received the M.Sc. degree in computer science with top honors from the University of Bologna. He has wide experience in project management and software development in logistics systems. He is a consultant, involved in programming software core modules for railways network diagnostics systems. Xiaoqun Wang (“ Quasi-Monte Carlo Methods in Financial Engineering: An Equivalence Principle and Dimension Reduction ”) is a professor at the Department of Mathematical Sciences of Tsinghua University, Beijing, China. His main research interests include quantitative and computational finance, quasi-Monte Carlo methods (or low discrepancy simulation) and efficiency improvement via variance reduction and dimension reduction. The paper in this issue is a part of an ongoing project on developing efficient quasi-Monte Carlo algorithms and dimension reduction methods for high-dimensional asset pricing and risk management problems in finance. Di Yuan (“ Solving Nonlinear Covering Problems Arising in WLAN Design ”) received his M.Sc. degree in computer science and engineering and Ph.D. degree in operations research at Linköping Institute of Technology, Sweden, in 1996 and 2001, respectively. In 2005 he received Docent (habilitation) degree. Since 2009 he has been a full professor in telecommunications at the Department of Science and Technology, Linköping University, Sweden. His research interests span design, analysis, and resource optimization of telecommunication systems. He has published over 20 refereed articles in international journals and over 40 refereed articles in IEEE and ACM conferences. His current research addresses network design and bandwidth allocation of 3G/4G cellular systems, and resource management in ad hoc and mesh networks. Assaf Zeevi (“ On the Minimax Complexity of Pricing in a Changing Environment ”) is the Kravis Professor of Business in the Graduate School of Business, Columbia University. His main research focuses on stochastic modeling and statistics and their applications in service operations, revenue management, financial engineering, and applied probability.