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Multicut Benders decomposition algorithm for process supply chain planning under uncertainty
10 references·12 citing·41 second hop
Multicut Benders decomposition algorithm for process supply chain planning under uncertainty (2011)Multicut Benders decomposition algorithm …Introduction to Stochastic Programming (2011)Introduction to Stochastic Pr…Benders Decomposition for Large-Scale Uncapacitated Hub Location (2011)Benders Decomposition for Lar…Stochastic programming approach to optimization under uncertainty (2007)Stochastic programming approa…The empirical behavior of sampling methods for stochastic programming (2006)The empirical behavior of sam…A stochastic programming approach for supply chain network design under uncertainty (2004)A stochastic programming appr…A simulation-based approach to two-stage stochastic programming with recourse (1998)A simulation-based approach t…Introduction to Stochastic Programming (1997)Introduction to Stochastic Pr…Planning under uncertainty solving large-scale stochastic linear programs (1992)Planning under uncertainty so…Monte Carlo (importance) sampling within a benders decomposition algorithm for stochastic linear programs (1992)Monte Carlo (importance) samp…Stochastic Decomposition: An Algorithm for Two-Stage Linear Programs with Recourse (1991)Stochastic Decomposition: An …Capacitated Mobile Facility Location Problem with Mobile Demand: Efficient Relief Aid Provision to En Route Refugees (2024)Capacitated Mobile Facility L…An integrated supply chain network design for advanced air mobility aircraft manufacturing using stochastic optimization (2024)An integrated supply chain ne…A Benders decomposition algorithm for the maximum availability service facility location problem (2022)A Benders decomposition algor…Budgeting in International Humanitarian Organizations (2021)Budgeting in International Hu…Developing childhood vaccine administration and inventory replenishment policies that minimize open vial wastage (2019)Developing childhood vaccine …A hybrid robust stochastic programming for a bi-objective blood collection facilities problem (Case study: Iranian blood transfusion network) (2019)A hybrid robust stochastic pr…A scenario-based stochastic programming approach for the product configuration problem under uncertainties and carbon emission regulations (2018)A scenario-based stochastic p…A multi-echelon multi-product stochastic model to supply chain of small-and-medium enterprises in industrial clusters (2017)A multi-echelon multi-product…Benders’ decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties (2015)Benders’ decomposition for co…Process Supply Chains Management – Where are We? Where to Go Next? (2014)Process Supply Chains Managem…Design of Resilient Supply Chains with Risk of Facility Disruptions (2014)Design of Resilient Supply Ch…Robust Scenario Formulations for Strategic Supply Chain Optimization under Uncertainty (2013)Robust Scenario Formulations …Linear Programming under Uncertainty (1955)Scenarios and Policy Aggregation in Optimization Under Uncertainty (1991)Production planning via scenario modelling (1993)Network planning with random demand (1994)Cut sharing for multistage stochastic linear programs with interstage dependency (1996)Linear Programming Under Uncertainty (2004)On the Rate of Convergence of Optimal Solutions of Monte Carlo Approximations of Stochastic Programs (2000)Stochastic Programming (2010)Monte Carlo sampling-based methods for stochastic optimization (2014)Robust Stochastic Optimization Made Easy with RSOME (2020)Large Sample Properties of Simulations Using Latin Hypercube Sampling (1987)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)The Sample Average Approximation Method for Stochastic Discrete Optimization (2002)On Complexity of Stochastic Programming Problems (2006)Planning for Disruptions in Supply Chain Networks (2006)Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs (1985)A unified framework for stochastic optimization (2018)PORTFOLIO SELECTION* (1952)Coherent Measures of Risk (1999)Optimization of conditional value-at-risk (2000)Strong Duality in Robust Convex Programming: Complete Characterizations (2010)Modeling approaches for the design of resilient supply networks under disruptions (2011)A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice (2019)Strategic facility location: A review (1998)The Ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management (2013)Literature review on disruption recovery in the supply chain (2017)Supply chain network design under uncertainty: A comprehensive review and future research directions (2017)Integer programming formulations of discrete hub location problems (1994)Network hub location problems: The state of the art (2007)Multicommodity Distribution System Design by Benders Decomposition * † ‡ (2010)Stochastic uncapacitated hub location (2011)Hub location under uncertainty (2012)Perspectives on modeling hub location problems (2020)Conditional value-at-risk for general loss distributions (2002)Theory and Applications of Robust Optimization (2010)Dynamic stochastic programmingfor asset-liability management (1998)Formulation of the Russell-Yasuda Kasai Financial Planning Model (1998)Call Center Staffing with Simulation and Cutting Plane Methods (2004)Robust optimization – A comprehensive survey (2007)Distributionally Robust Optimization and Its Tractable Approximations (2010)Quantitative models for managing supply chain risks: A review (2015)
this work references cited by second hop

References

  • 2011Introduction to Stochastic Programming6,469 cited
  • 2004A stochastic programming approach for supply chain network design under uncertainty1,131 cited
  • 1997Introduction to Stochastic Programming959 cited
  • 1991Stochastic Decomposition: An Algorithm for Two-Stage Linear Programs with Recourse452 cited
  • 2006The empirical behavior of sampling methods for stochastic programming426 cited
  • 1998A simulation-based approach to two-stage stochastic programming with recourse290 cited
  • 2011Benders Decomposition for Large-Scale Uncapacitated Hub Location239 cited
  • 1992Planning under uncertainty solving large-scale stochastic linear programs220 cited
  • 2007Stochastic programming approach to optimization under uncertainty210 cited
  • 1992Monte Carlo (importance) sampling within a benders decomposition algorithm for stochastic linear programs209 cited

Cited by

  • 2015Benders’ decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties112 cited
  • 2014Design of Resilient Supply Chains with Risk of Facility Disruptions93 cited
  • 2014Process Supply Chains Management – Where are We? Where to Go Next?50 cited
  • 2021Budgeting in International Humanitarian Organizations40 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2013Robust Scenario Formulations for Strategic Supply Chain Optimization under Uncertainty30 cited
  • 2018A scenario-based stochastic programming approach for the product configuration problem under uncertainties and carbon emission regulations29 cited
  • 2017A multi-echelon multi-product stochastic model to supply chain of small-and-medium enterprises in industrial clusters22 cited
  • 2022A Benders decomposition algorithm for the maximum availability service facility location problem20 cited
  • 2019Developing childhood vaccine administration and inventory replenishment policies that minimize open vial wastage18 cited
  • 2019A hybrid robust stochastic programming for a bi-objective blood collection facilities problem (Case study: Iranian blood transfusion network)17 cited
  • 2024Capacitated Mobile Facility Location Problem with Mobile Demand: Efficient Relief Aid Provision to En Route Refugees17 cited
  • 2024An integrated supply chain network design for advanced air mobility aircraft manufacturing using stochastic optimization12 cited