Author
Matoğlu, Melda Örmeci, Vate, J. V.
Publication Date
2011
Publication Place
-
Informs
Subject
Inventory/production, Stochastic, Stochastic model applications
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
0030-364X
Record ID
68f04ab4-890d-4f5e-8cf9-cc235b6f85fe
Library Location
International Finance
Date
2011
Notes
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text
We model the problem of managing capacity in a build-to-order environment as a Brownian drift control problem and seek a policy that minimizes the long-term average cost. We assume the controller can, at some cost, shift the processing rate among a finite set of alternatives, for example by adding or removing staff, increasing or reducing the number of shifts, or opening or closing production lines. The controller incurs a cost for capacity per unit time and a delay cost that reflects the opportunity cost of revenue waiting to be recognized or the customer service impacts of delaying delivery of orders. Furthermore, he incurs a cost per unit to reject orders or idle resources as necessary to keep the workload of waiting orders within a prescribed range. We introduce a practical restriction on this problem, called the S-restricted Brownian control problem, and show how to model it via a structured linear program. We demonstrate that an optimal solution to the S-restricted problem can be found among a special class of policies called deterministic nonoverlapping control band policies. These results exploit apparently new relationships between complementary dual solutions and relative value functions that allow us to obtain a lower bound on the average cost of any nonanticipating policy for the problem, even without the S restriction. Under mild assumptions on the cost parameters, we show that our linear programming approach is asymptotically optimal for the unrestricted Brownian control problem in the sense that by appropriately selecting the S-restricted problem, we can ensure its solution is within an arbitrary finite tolerance of a lower bound on the average cost of any nonanticipating policy for the unrestricted Brownian control problem.
DOI
10.1287/opre.1100.0868
Cilt
59
