Inventory control in a fluctuating demand environment
Operations Research
Robust Solutions to Least-Squares Problems with Uncertain Data
SIAM Journal on Matrix Analysis and Applications
Mathematics of Operations Research
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Robust Solutions to Uncertain Semidefinite Programs
SIAM Journal on Optimization
A Single-Item Inventory Model for a Nonstationary Demand Process
Manufacturing & Service Operations Management
On the Relation Between Option and Stock Prices: A Convex Optimization Approach
Operations Research
Operations Research
Adjustable robust solutions of uncertain linear programs
Mathematical Programming: Series A and B
Learning Algorithms for Separable Approximations of Discrete Stochastic Optimization Problems
Mathematics of Operations Research
Tractable Approximations to Robust Conic Optimization Problems
Mathematical Programming: Series A and B
A Robust Optimization Approach to Dynamic Pricing and Inventory Control with no Backorders
Mathematical Programming: Series A and B
Approximate Solutions of a Dynamic Forecast-Inventory Model
Manufacturing & Service Operations Management
Retailer-Supplier Flexible Commitments Contracts: A Robust Optimization Approach
Manufacturing & Service Operations Management
A Robust Optimization Approach to Inventory Theory
Operations Research
Convex Approximations of Chance Constrained Programs
SIAM Journal on Optimization
Approximation Algorithms for Stochastic Inventory Control Models
Mathematics of Operations Research
Provably Near-Optimal Sampling-Based Policies for Stochastic Inventory Control Models
Mathematics of Operations Research
A Robust Optimization Perspective on Stochastic Programming
Operations Research
A Linear Decision-Based Approximation Approach to Stochastic Programming
Operations Research
Operations Research
Conic mixed-integer rounding cuts
Mathematical Programming: Series A and B
Computing robust basestock levels
Discrete Optimization
Robust solutions of uncertain linear programs
Operations Research Letters
Robust linear optimization under general norms
Operations Research Letters
Distributionally Robust Optimization and Its Tractable Approximations
Operations Research
Fully Distribution-Free Profit Maximization: The Inventory Management Case
Mathematics of Operations Research
Robust Optimization Made Easy with ROME
Operations Research
Robust Inventory Routing Under Demand Uncertainty
Transportation Science
Robust Storage Assignment in Unit-Load Warehouses
Management Science
Robust Modified Policy Iteration
INFORMS Journal on Computing
Using robust optimization for distribution and inventory planning for a large pulp producer
Computers and Operations Research
| Hi-index | 0.00 |
We propose a robust optimization approach to address a multiperiod inventory control problem under ambiguous demands, that is, only limited information of the demand distributions such as mean, support, and some measures of deviations. Our framework extends to correlated demands and is developed around a factor-based model, which has the ability to incorporate business factors as well as time-series forecast effects of trend, seasonality, and cyclic variations. We can obtain the parameters of the replenishment policies by solving a tractable deterministic optimization problem in the form of a second-order cone optimization problem (SOCP), with solution time; unlike dynamic programming approaches, it is polynomial and independent on parameters such as replenishment lead time, demand variability, and correlations. The proposed truncated linear replenishment policy (TLRP), which is piecewise linear with respect to demand history, improves upon static and linear policies, and achieves objective values that are reasonably close to optimal.