Distribution-dependent robust linear optimization with applications to inventory control.
This paper tackles linear programming problems with data uncertainty and applies it to an important inventory control problem. Each element of the constraint matrix is subject to uncertainty and is modeled as a random variable with a bounded support. The classical robust optimization approach to this problem yields a solution with guaranteed feasibility. As this approach tends to be too conservative when applications can tolerate a small chance of infeasibility, one would be interested in obtaining a less conservative solution with a certain probabilistic guarantee of feasibility. A robust formulation in the literature produces such a solution, but it does not use any distributional information on the uncertain data. In this work, we show that the use of distributional information leads to an equally robust solution (i.e., under the same probabilistic guarantee of feasibility) but with a better objective value. In particular, by exploiting distributional information, we establish stronger upper bounds on the constraint violation probability of a solution. These bounds enable us to "inject" less conservatism into the formulation, which in turn yields a more cost-effective solution (by 50% or more in some numerical instances). To illustrate the effectiveness of our methodology, we consider a discrete-time stochastic inventory control problem with certain quality of service constraints. Numerical tests demonstrate that the use of distributional information in the robust optimization of the inventory control problem results in 36%-54% cost savings, compared to the case where such information is not used.
The Korea Transport Institute, Goyang-si, Korea, jsckang@koti.re.krM.
Seong-Cheol
SC
Kang
Department of Electrical & Computer Eng., Boston University, Boston, MA 02215, USA, tbrisimi@bu.edu.
Theodora S
TS
Brisimi
Department of Electrical & Computer Eng. and Division of Systems Eng., Boston University, Boston, MA 02215, USA, yannisp@bu.edu , url: http://ionia.bu.edu/
Ioannis Ch
IC
Paschalidis
Data uncertainty; Inventory Control; Linear programming; Quality-of-Service; Robust optimization