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Enregistrement W4213252392 · doi:10.1287/opre.1120.1076

Contributors

2012· article· en· W4213252392 sur OpenAlexaboutno aff

Notice bibliographique

RevueOperations Research · 2012
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueAdvanced Queuing Theory Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer science

Résumé

récupéré en direct d'OpenAlex

Ivo Adan (“ Exact FCFS Matching Rates for Two Infinite Multitype Sequences ”) is a full professor of manufacturing networks in the Department of Mechanical Engineering at the Eindhoven University of Technology. His current research focuses on the modeling, analysis, and design of manufacturing, warehousing, and healthcare systems, and more specifically, the analysis of multidimensional Markov processes and queueing models. Alper Atamtürk (“ A Conic Integer Programming Approach to Stochastic Joint Location-Inventory Problems ”) is a Chancellor's Professor in the Industrial Engineering and Operations Research Department at the University of California, Berkeley. His current research interests are in optimization, integer programming, optimization under uncertainty with applications to energy, finance, operations, cancer therapy, and defense. He was appointed a National Security Fellow by the United States Department of Defense in 2010. Rami Atar (“ A Diffusion Regime with Nondegenerate Slowdown ”) is a professor in the Department of Electrical Engineering, Technion, Israel. His research interests are in stochastic processes. These include asymptotic analysis of queueing and stochastic network models in diffusion and large deviation regimes, PDE techniques in stochastic control and differential games, filtering, and estimation. Derek Atkins (“ A Simulation Optimization Approach to Long-Term Care Capacity Planning ”) is a professor in the Sauder School of Business at the University of British Columbia, Canada. His research interests are in supply chains and healthcare operations. He was formerly director of the Centre for Operations Excellence at Sauder, which undertook a project for a local health authority that triggered the need for the paper presented in this issue. Gemma Berenguer (“ A Conic Integer Programming Approach to Stochastic Joint Location-Inventory Problems ”) is a Ph.D. candidate in the Industrial Engineering and Operations Research Department at the University of California, Berkeley. She is doing research on integrated supply chain design problems, nonprofit supply chain management problems, and the design of regulatory mechanisms for environmental policies. Ya Ping Fang (“ Piecewise Linear Multicriteria Programs: The Continuous Case and Its Discontinuous Generalization ”) is an associate professor in the Department of Mathematics at Sichuan University. His research interests are in the area of optimization problems, equilibrium problems, and variational inequalities. Michael C. Fu (“ A New Stochastic Derivative Estimator for Discontinuous Payoff Functions with Application to Financial Derivatives ”) is the Ralph J. Tyser Professor of Management Science in the Robert H. Smith School of Business at the University of Maryland. His research interests include simulation and applied probability modeling, particularly with applications toward manufacturing systems, supply chain management, and financial engineering. He is a Fellow of INFORMS and IEEE. David Gamarnik (“ Belief Propagation for Min-Cost Network Flow: Convergence and Correctness ”) is an associate professor of operations research at the Sloan School of Management at the Massachusetts Institute of Technology. His research interests include applied probability and stochastic processes, theory of random graphs and algorithms, combinatorial optimization, statistical learning theory, and various applications. He is a recipient of the Erlang Prize from the INFORMS Applied Probability Society, IBM Faculty Partnership Award, and several NSF-sponsored grants. Nir Halman (“ Approximating the Nonlinear Newsvendor and Single-Item Stochastic Lot-Sizing Problems When Data Is Given by an Oracle ”) is a lecturer of operations research in the school of business administration at the Hebrew University of Jerusalem. His research focuses on optimization methods that yield efficient algorithms in combinatorial optimization. Jonathan Kluberg (“ Generalized Quantity Competition for Multiple Products and Loss of Efficiency ”) is an investment analyst at High Vista Strategies. Yuri Levin (“ Cargo Capacity Management with Allotments and Spot Market Demand ”) is a Distinguished Professor of Operations Management at Queen's School of Business in Kingston, Ontario, Canada. His research interests include revenue management, dynamic pricing, numerical optimization, and machine learning applications. Qing Li (“ On the Quasiconcavity of Lost-Sales Inventory Models with Fixed Costs ”) is an associate professor at the School of Business and Management, Hong Kong University of Science and Technology. His research interests include supply chain management, marketing/operations interfaces, stochastic dynamic inventory models, and economics of waste. Steven I. Marcus (“ A New Stochastic Derivative Estimator for Discontinuous Payoff Functions with Application to Financial Derivatives ”) is a professor in the Department of Electrical and Computer Engineering and the Institute for Systems Research at the University of Maryland. His research focuses on stochastic control and estimation, with applications in manufacturing and telecommunication networks. Kaiwen Meng (“ Piecewise Linear Multicriteria Programs: The Continuous Case and Its Discontinuous Generalization ”) holds a Ph.D. degree (2011) in optimization and operations research from the Hong Kong Polytechnic University. His research interests are in the areas of variational analysis, optimization theory, and operations research. S. Michel (“ A Column-Generation Based Tactical Planning Method for Inventory Routing ”) is an assistant professor of operations research at Le Havre University. She is a member of the Laboratory of Applied Mathematics and the Logistics Engineering Institute and an associate member of the INRIA research team REALOPT. Her research projects concern sea ship and vehicle routing, as well as generic primal heuristics. Anton Molyboha (“ Stochastic Optimization of Sensor Placement for Diver Detection ”) is a quantitative analyst at Teza Technologies. He holds a Ph.D. degree in mathematics with concentration in stochastic systems (2009) from the Department of Mathematical Sciences at Stevens Institute of Technology. Mikhail Nediak (“ Cargo Capacity Management with Allotments and Spot Market Demand ”) is an assistant professor in the School of Business at Queen's University in Kingston, Ontario, Canada. His research focuses on new models in revenue management and dynamic pricing. Matthew Nelson (“ A Simulation Optimization Approach to Long-Term Care Capacity Planning ”) is a project lead in the Centre for Research in Healthcare Engineering at the University of Toronto. He received his master's degree from the Centre for Operations Excellence in the Sauder School of Business at the University of British Columbia. James B. Orlin (“ Approximating the Nonlinear Newsvendor and Single-Item Stochastic Lot-Sizing Problems When Data Is Given by an Oracle ”) is the Edward Pennell Brooks Professor of Operations Research in the Sloan School of Management at the Massachusetts Institute of Technology. His research focuses on optimization methods, especially in combinatorial and network optimization. He is a coauthor of Network Flows: Theory, Algorithms, and Applications (Prentice-Hall, 1993), for which he was awarded the Lanchester Prize in 1993. He is an INFORMS Fellow. Georgia Perakis (“ Generalized Quantity Competition for Multiple Products and Loss of Efficiency ”) is the William F. Pounds Professor at the Sloan School of Management at Massachusetts Institute of Technology. Dzung T. Phan (“ Lagrangian Duality and Branch-and-Bound Algorithms for Optimal Power Flow ”) is a research staff member in the Mathematical Sciences Department at IBM T. J. Watson Research Center, Yorktown Heights, New York, where he spent one year as a postdoctoral researcher. His research interests lie in the field of optimization theory and algorithms. Recently at IBM, he developed several numerical algorithms for optimization problems arising from power system analysis. Martin L. Puterman (“ A Simulation Optimization Approach to Long-Term Care Capacity Planning ”) is Advisory Board Professor of Operations in the Sauder School of Business at the University of British Columbia, Canada. He was founder and director of the Centre for Operations Excellence (in Sauder), the UBC Centre for Health Care Management, and the Biostatistical Consulting Service at BC Children's Hospital. He received the INFORMS Lanchester Prize for his book Markov Decision Processes: Discrete Stochastic Dynamic Programming (Wiley-Interscience, 2005). He is an INFORMS Fellow and recipient of the Canadian Operations Research Society (CORS) Award of Merit, the CORS Practice Prize, and the INFORMS case prize. Richard Ratliff (“ Estimating Primary Demand for Substitutable Products from Sales Transaction Data ”) is the Senior Research Scientist at Sabre Research. His primary focus is on applied research and development in travel revenue management. His work has included prototyping new technologies applicable to travel distribution, as well as major travel suppliers. Devavrat Shah (“ Belief Propagation for Min-Cost Network Flow: Convergence and Correctness ”) is a Jamieson career development associate professor in the Department of Electrical Engineering and Computer Science at Massachusetts Institute of Technology. He is a member of the Laboratory for Information and Decision Systems and Operations Research Center. His research focus is on theory of large complex net

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,970
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,002
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,005

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,077
Tête enseignante GPT0,380
Écart entre enseignants0,303 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

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