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Operations & Supply Chain Management

See the latest research, articles and faculty on the Operations & Supply Chain Management Area of Expertise at Columbia Business School.

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Latest on Operations & Supply Chain Management

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Operations & Supply Chain Management Faculty

CBS Faculty Research on Operations & Supply Chain Management

On the accuracy of the simple peak hour approximation for Markovian queues

Authors
Linda Green and Peter Kolesar
Date
August 1, 1995
Format
Journal Article
Journal
Management Science

We empirically explore the accuracy of the simple stationary peak hour approximation (SPHA) for estimating peak hour performance in multiserver queuing systems with exponential service times and periodic (sinusoidal) Poisson arrival processes. We show that the SPHA is very good for a range of parameter values corresponding to a reasonably broad spectrum of real systems. However, we do find and document that there are many situation in which this approximation will be very inaccurate.

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The Impact of Bundle Type Price Framing and Familiarity on Evaluation of the Bundle

Authors
Bari Harlam, Aradhna Krishna, Donald Lehmann, and Carl Mela
Date
May 1, 1995
Format
Journal Article
Journal
Journal of Business Research

Bundling of products is very prevalent in the marketplace. For example, travel packages include airfare, lodging, and a rental car. Considerable economic research has focused on the change in profits and consumer surplus that ensues if bundles are offered. There is relatively little research in marketing that deals with bundling, however. In this article we concentrate on some tactical issues of bundling, such as which types of products should be bundled, what price one can charge for the bundle, and how the price of the bundle should be presented to consumers to improve purchase intent.

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Fast solution and detection of minimal forecast horizons in dynamic programs with a single indicator of the future: Applications to dynamic lot-sizing models

Authors
Awi Federgruen and Michal Tzur
Date
May 1, 1995
Format
Journal Article
Journal
Management Science

In most dynamic planning problems, one observes that an optimal decision at any given stage depends on limited information, i.e. information pertaining to a limited set of adjacent or nearby stages. This holds in particular for planning problems over time, where an optimal decision in a given period depends on information related to a limited future time horizon, a so-called forecast horizon, only. In this paper we identify a general class of dynamic programs in which an efficient forward algorithm can be designed to solve the problem and to identify minimal forecast horizons.

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Hedging-point production control with multiple failure modes

Authors
Paul Glasserman
Date
April 1, 1995
Format
Journal Article
Journal
IEEE Transactions on Automatic Control

We consider the control of a production facility subject to multiple failure modes. Motivated by a work of Akella-Kumar (1986) and Bielecki-Kumar (1988) on single-failure-mode models, we study hedging-point policies, in which production is controlled to its maximum rate whenever inventory is below a critical level and set to zero whenever inventory is above that level. The maximum production rate varies with the state of the machine.

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Do Tax Reforms Affect Investment?

Authors
Jason Cummins, Kevin Hassett, and R. Glenn Hubbard
Date
January 1, 1995
Format
Chapter
Book
Tax Policy and the Economy

We improve upon existing approaches used to estimate investment models by exploiting tax reforms as "natural experiments." we find that tax policy has an economically important effect through the user cost of capital on firms' equipment investment following major tax reforms enacted in 1962, 1971, 1981, and 1986. This effect is most pronounced for firms not in tax loss positions and, thus, more likely to face statutory tax rates and investment incentives.

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Efficient algorithms for finding optimal power-of-two policies for production/distribution systems with general joint setup costs

Authors
Awi Federgruen and Yu-Sheng Zheng
Date
January 1, 1995
Format
Journal Article
Journal
Operations Research

We consider a production/distribution system represented by a general directed acyclic network. Each node is associated with a specific "product" at a given location and/or production stage. An arc (i, j) indicates that item i is used to "produce" item j. External demands may occur at any of the network's nodes. These demands occur continuously at item-specific constant rates. Components may be assembled in any given proportions. The cost structure consists of inventory carrying, viable, and fixed production/distribution costs.

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Note: On the efficiency of imbalance in multi-facility multi-server service systems

Authors
Linda Green and Debashis Guha
Date
January 1, 1995
Format
Journal Article
Journal
Management Science

We consider the problem of simultaneously allocating servers and demands in a service system with independent multiple facilities. We assume a fixed number of facilities and total servers which must service a given Poisson arrival stream. We also assume that service times are identically distributed and independent of the server or facility. The allocation decision is one of simultaneously determining the number of servers and the fraction of the total arrival stream for each facility in order to optimize a givne performance measure.

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Budget

Authors
Raymond Horton
Date
January 1, 1995
Format
Chapter
Book
Encyclopedia of New York City
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Greedy heuristics for single-machine scheduling problems with general earliness and tardiness costs

Authors
Awi Federgruen and Gur Mosheiov
Date
November 1, 1994
Format
Journal Article
Journal
Operations Research Letters

This paper addresses a class of single-machine scheduling problems with a common due-date for all jobs, and general earliness and tardiness costs. We show that a class of simple, polynomial, "greedy-type" heuristics can be used to generate close-to-optimal schedules. An extensive numerical study exhibits small optimality gaps. For convex cost structures, we establish that the worst-case optimality gap is bounded by e−i ≈ 0.36, if the due-date is non-restrictive.

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