Managing congestion in a multi-modal transportation network under biomass supply uncertainty

DOI10.1007/s10479-017-2499-yzbMath1410.90016OpenAlexW2609915266MaRDI QIDQ1730690

Linkan Bian, Mohammad Marufuzzaman, Reuben F. V Burch, Sushil R. Poudel, Md Abdul Quddus

Publication date: 6 March 2019

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-017-2499-y

zbMATH Keywords

sample average approximationprogressive hedging algorithmbiomass supply chain networkconstraint-generation algorithmmulti-modal facilitiesrolling horizon heuristics

Mathematics Subject Classification ID

Stochastic programming (90C15) Approximation methods and heuristics in mathematical programming (90C59) Inventory, storage, reservoirs (90B05)

Uses Software

• GAMS

Cites Work

• Multimodal freight transportation planning: a literature review
• Efficient solution of a class of location-allocation problems with stochastic demand and congestion
• Two-stage stochastic programming supply chain model for biodiesel production via wastewater treatment
• Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems
• Applying the progressive hedging algorithm to stochastic generalized networks
• Multiple allocation hub-and-spoke network design under hub congestion
• Supply chain design under uncertainty using sample average approximation and dual decomposition
• Using scenario trees and progressive hedging for stochastic inventory routing problems
• Approximate scenario solutions in the progressive hedging algorithm. A numerical study with an application to fisheries management
• Structural properties of the progressive hedging algorithm
• A branch and bound method for stochastic global optimization
• Monte Carlo bounding techniques for determinig solution quality in stochastic programs
• Location models for airline hubs behaving as \(M/D/c\) queues.
• Hub-and-spoke network design with congestion
• The sample average approximation method applied to stochastic routing problems: a computational study
• A stochastic programming approach for supply chain network design under uncertainty
• On Optimal Allocation of Indivisibles Under Uncertainty
• The Sample Average Approximation Method for Stochastic Discrete Optimization
• A Lagrangean Heuristic for Hub-and-Spoke System Design with Capacity Selection and Congestion
• Progressive hedging-based metaheuristics for stochastic network design
• The Latest Arrival Hub Location Problem
• Scenarios and Policy Aggregation in Optimization Under Uncertainty
• Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria