Volume 4:1

Copies of these published papers may be downloaded from Informs Online


The MSOM Society Student Paper Competition:  Extended Abstracts of 2001 Winners


Title: "Forecast, Solution and Rolling Horizons in Operations Management: A Classified Bibliography"

Author(s): Suresh Chand, Suresh Sethi, Vernon Hsu

Abstract: We present a classified bibliography of the literature in the area of forecast, solution, and rolling horizons primarily in operations management problems. Each of over 200 selected papers is categorized on five dimensions that identify the horizon type, the model type (deterministic or stochastic), the sources of horizon, the methods used to obtain horizon results, and the subject area of the paper. The majority of the papers treat dynamic problems in inventory management, production planning, capacity expansion, machine replacement, and warehousing.

(Horizons, Operations Management, Dynamic Programming)

The Consulting Senior Editor was Joseph Thomas

The manuscript was submitted on September 12 2001. The average review cycle time was 23 days.

Corresponding author: Suresh Chand, Purdue University, Krannert School of Management. 1310 Krannert Building, West Lafayette, IN 47907-1310 Phone: 765-494-4530, E-mail: suresh@mgmt.purdue.edu


Title: Dynamic Capacity Expansion Problem with Deferred Expansion and Age-Dependent Shortage Cost

Author(s): Vernon Hsu

Abstract: Deferring capacity expansion may be a cost effective decision when there is anticipation of cheaper capacity in the near future and/or there is lack of economies of scale in demand to justify the current expansion. This paper studies a finite-period capacity expansion problem (CEP) with deferred capacity expansion. The operating, shortage costs and the cost of holding unused capacity all depend on the period in which the capacity is acquired.

Our model is a generalization of the Wagner-Whitin formulation of the CEP and an extension (with deferred expansion) of two other polynomially solvable CEPs in the literature.  We explore structural properties of the problem and develop an efficient dynamic programming algorithm to solve the problem in polynomial time.

The Consulting Senior Editor was Suresh Chand

The manuscript was submitted on June 11, 2001 subject to five  reviews with 95 days in revision. The average review cycle time was 29 days.

Corresponding author: Vernon Hsu, Hong Kong University of Science and Technology, PDepartment of IEEM, Clearwater Bay, Kowloon Hong Kong.  Phone: 852-2358-7118, Fax: 852-2774-3679. E-mail: vhsu@ust.hk


Title: "Gaining Benefits from Joint Forecasting and Replenishment Processes: The Case of Auto-correlated Demand"

Author(s): Yossi Aviv

Abstract: In this paper we consider a cooperative, two-level supply chain consisting of a retailer and a supplier. As in many practical settings, the supply chain members progressively observe market signals that enable them to explain future demand. The demand itself evolves according to an auto-regressive time series. We examine three types of supply chain configurations. In the first setting, the retailer and the supplier coordinate their policy parameters in an attempt to minimize system-wide costs, but they do not share their observations of market signals. In the second setting, resembling many original Vendor-Managed Inventory (VMI) programs, the supplier takes the full responsibility of managing the supply chain’s inventory, but the retailer’s observations of market signals are not transferred to him. In our third setting, reminiscent of Collaborative Forecasting and Replenishment partnerships, inventory is managed centrally, and all demand related information is shared. We propose a set of stylized models to study the three settings and use them to provide managerial insights into the value of information sharing, VMI, and Collaborative Forecasting.

The Consulting Senior Editor was Hau Lee

The manuscript was submitted on December 30, 1999. The average review cycle time was 60.5 days.

Corresponding author: Yossi Aviv, Washington University, The John M. Olin School of Business, Campus Box 1133, One Brookings Drive, St. Louis, MO. 63130-4899 Phone: 314-935-6396, Fax: 314-935-6359, E-mail: AVIV@olin.wustl.edu


Title: Heuristic Methods for Centralized Control of One-Warehouse N-Retailer Inventory Systems

Author(s): Sven Axsater, Johan Marklund, Edward Silver

Abstract: This paper considers a periodic review two-echelon arborescent inventory system with one central warehouse and a number of retailers facing stochastic demand. The retailers replenish from the warehouse, and the warehouse from an outsider supplier with infinite supply. Transportation times are constant. No ordering costs are considered, but warehouse replenishments must be multiples of a given batch quantity. The objective is to minimize holding and backorder costs. The standard approach to approximately solve this problem is to use a “balance” assumption meaning that negative stock allocations to the retailers are assumed possible. This approach may lead to considerable errors for problems with large differences between the retailers, in terms of service requirements and demand characteristics. To handle such situations we suggest and evaluate two computationally tractable heuristics: the Virtual Assignment ordering rule for warehouse replenishments, and the Two-step Allocation rule for allocating stock from the warehouse to the retailers. Numerical evidence shows that especially when combining both heuristics we obtain considerable improvements for many problems compared to the standard approach. Savings of up to 50% have been recorded.

The Consulting Senior Editor was Paul Zipkin.

The manuscript was submitted on October 23, 1998, subject to seven  reviews with 706 days in revision. The average review cycle time was 59 days.

Corresponding author: Sven Axsater, Lund University, Department of Industrial Engineering, PO Box 118, S-221 00 Lund, Sweden. Phone: 46-46-22-23-387, Fax: 46-46-22-24-619. E-mail: Sven.Axsater@ie.lth.se


Copies of these published papers may be downloaded from Informs Online