Stochastic decomposition: an algorithm for two-state linear programs with recourse
Mathematics of Operations Research
Dynamic and stochastic models for the allocation of empty containers
Operations Research
The fleet assignment problem: solving a large-scale integer program
Mathematical Programming: Series A and B
Journal of Optimization Theory and Applications
Dynamic Control of Logistics Queueing Networks for Large-Scale Fleet Management
Transportation Science
Improved Empty Freight Car Distribution
Transportation Science
Learning Algorithms for Separable Approximations of Discrete Stochastic Optimization Problems
Mathematics of Operations Research
The optimizing-simulator: merging simulation and optimization using approximate dynamic programming
WSC '05 Proceedings of the 37th conference on Winter simulation
The optimizing-simulator: merging simulation and optimization using approximate dynamic programming
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Dynamic modeling and control of supply chain systems: A review
Computers and Operations Research
Approximate dynamic programming: lessons from the field
Proceedings of the 40th Conference on Winter Simulation
An Optimal Approximate Dynamic Programming Algorithm for the Lagged Asset Acquisition Problem
Mathematics of Operations Research
Robust Optimization for Empty Repositioning Problems
Operations Research
Approximate Dynamic Programming for Ambulance Redeployment
INFORMS Journal on Computing
QoS-based cooperative algorithm for integral multi-commodity flow problem
Computer Communications
The Effect of Robust Decisions on the Cost of Uncertainty in Military Airlift Operations
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A polynomial-time algorithm for optimizing over N-flod 4-block decomposable integer programs
IPCO'10 Proceedings of the 14th international conference on Integer Programming and Combinatorial Optimization
SMART: A Stochastic Multiscale Model for the Analysis of Energy Resources, Technology, and Policy
INFORMS Journal on Computing
A dynamic programming approximation for downlink channel allocation in cognitive femtocell networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
| Hi-index | 0.00 |
In this paper, we consider a stochastic and time-dependent version of the min-cost integer multicommodity-flow problem that arises in the dynamic resource allocation context. In this problem class, tasks arriving over time have to be covered by a set of indivisible and reusable resources of different types. The assignment of a resource to a task removes the task from the system, modifies the resource, and generates a profit. When serving a task, resources of different types can serve as substitutes of each other, possibly yielding different revenues. We propose an iterative, adaptive dynamic-programming-based methodology that makes use of linear or nonlinear approximations of the value function. Our numerical work shows that the proposed method provides high-quality solutions and is computationally attractive for large problems.