David Simchi-Levi

David Simchi-Levi is an American academic working as a Professor of Engineering Systems at Massachusetts Institute of Technology. He is also the founder or co-founder of several companies. Simchi-Levi's research focuses on supply chain management, revenue management, and business analytics. Provided by Wikipedia
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  1. 1
    Reengineering Management Science for a Sharper Focus and Broader Appeal
    by Simchi-Levi, David
    Published 2019
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  2. 2
    Competition in the Supply Option Market
    by Martinez-, Simchi-Levi, David
    Published 2012
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  3. 3
    Supplier-Buyer Negotiation Games: Equilibrium Conditions and Supply Chain Efficiency
    by Martinez-, Simchi-Levi, David
    Published 2013
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  4. 4
    The lingering of gradients: How to reuse gradients over time
    by simchi-levi, David, Wang, Xinshang
    Published 2021
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  5. 5
    A carbon-capped supply chain network problem
    by Diabat, Ali, Simchi-Levi, David
    Published 2010
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  6. 6
    Performance Evaluation of Stochastic Multi-Echelon Inventory Systems: A Survey
    by Simchi-Levi, David, Zhao, Yao
    Published 2012
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  7. 7
    Optimal static pricing for a tree network
    by Caro, Felipe, Simchi-Levi, David
    Published 2013
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  8. 8
    Worst-Case Analysis of Process Flexibility Designs
    by Simchi-Levi, David, Wei, Yehua
    Published 2016
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  9. 9
    A Simpler Way to Modernize Your Supply Chain How to spend less and accomplish more
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  10. 10
    A Simpler Way to Modernize Your Supply Chain How to spend less and accomplish more
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  11. 11
    Sampling-Based Approximation Schemes for Capacitated Stochastic Inventory Control Models
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  12. 12
    Powering retailers' digitization through analytics and automation
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  13. 13
    Designing Response Supply Chain Against Bioattacks
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  14. 14
    On Policies for Single-Leg Revenue Management with Limited Demand Information
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  15. 15
    Dynamic Inventory Allocation with Demand Learning for Seasonal Goods
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  16. 16
    Robust Stochastic Lot-Sizing by Means of Histograms
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  17. 17
    Multiship Crane Sequencing with Yard Congestion Constraints
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  18. 18
    Uplift Modeling with Multiple Treatments and General Response Types
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  19. 19
    Dynamic Learning and Pricing with Model Misspecification
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  20. 20
    Analyzing process flexibility: A distribution-free approach with partial expectations
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