Robust Solutions to Least-Squares Problems with Uncertain Data
SIAM Journal on Matrix Analysis and Applications
Mathematics of Operations Research
On the Relation Between Option and Stock Prices: A Convex Optimization Approach
Operations Research
Step decision rules for multistage stochastic programming: A heuristic approach
Automatica (Journal of IFAC)
Robust Optimization for Empty Repositioning Problems
Operations Research
Robust Controls for Network Revenue Management
Manufacturing & Service Operations Management
Wardrop Equilibria with Risk-Averse Users
Transportation Science
Dynamic Pricing and Inventory Control: Uncertainty and Competition
Operations Research
Robust Approximation to Multiperiod Inventory Management
Operations Research
Optimal Allocation of Surgery Blocks to Operating Rooms Under Uncertainty
Operations Research
Distributionally Robust Optimization and Its Tractable Approximations
Operations Research
Fully Distribution-Free Profit Maximization: The Inventory Management Case
Mathematics of Operations Research
Approximate dynamic programming for an inventory problem: Empirical comparison
Computers and Industrial Engineering
Regret in Overbooking and Fare-Class Allocation for Single Leg
Manufacturing & Service Operations Management
Production planning in furniture settings via robust optimization
Computers and Operations Research
Theory and Applications of Robust Optimization
SIAM Review
A negotiation framework for linked combinatorial optimization problems
Autonomous Agents and Multi-Agent Systems
A dynamic programming approach to adjustable robust optimization
Operations Research Letters
A belief-rule-based inventory control method under nonstationary and uncertain demand
Expert Systems with Applications: An International Journal
Computing robust basestock levels
Discrete Optimization
Robust Inventory Routing Under Demand Uncertainty
Transportation Science
Robust Storage Assignment in Unit-Load Warehouses
Management Science
Proceedings of the 2nd ACM international conference on High confidence networked systems
SDP reformulation for robust optimization problems based on nonconvex QP duality
Computational Optimization and Applications
Impact of the shape of demand distribution in decision models for operations management
Computers in Industry
| Hi-index | 0.00 |
We propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time. This problem has been studied in the past using dynamic programming, which suffers from dimensionality problems and assumes full knowledge of the demand distribution. The proposed approach takes into account the uncertainty of the demand in the supply chain without assuming a specific distribution, while remaining highly tractable and providing insight into the corresponding optimal policy. It also allows adjustment of the level of robustness of the solution to trade off performance and protection against uncertainty. An attractive feature of the proposed approach is its numerical tractability, especially when compared to multidimensional dynamic programming problems in complex supply chains, as the robust problem is of the same difficulty as the nominal problem, that is, a linear programming problem when there are no fixed costs, and a mixed-integer programming problem when fixed costs are present. Furthermore, we show that the optimal policy obtained in the robust approach is identical to the optimal policy obtained in the nominal case for a modified and explicitly computable demand sequence. In this way, we show that the structure of the optimal robust policy is of the same base-stock character as the optimal stochastic policy for a wide range of inventory problems in single installations, series systems, and general supply chains. Preliminary computational results are very promising.