Allocating Production Capacity Among Multiple Products

We consider the problem of allocating production capacity among multiple items, assuming that a fixed proportion of overall capacity can be dedicated exclusively to the production of each item. Given a capacity allocation, production of each item follows a base-stock policy, i.e., each demand trigge...

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Bibliographic Details
Published inOperations research Vol. 44; no. 5; pp. 724 - 734
Main Author Glasserman, Paul
Format Journal Article
LanguageEnglish
Published Linthicum, MD INFORMS 01.09.1996
Operations Research Society of America
Institute for Operations Research and the Management Sciences
Subjects
Allocations
Applied sciences
Approximation
Asymptotic properties
asymptotically optimal allocations
Average cost
Carrying costs
Cost allocation
Cost engineering
Cost functions
Exact sciences and technology
Inventories
Inventory control, production control. Distribution
inventory/production approximation
Manufacturing
Minimization of cost
Objective functions
Operational research and scientific management
Operational research. Management science
Operations research
Optimization
probability
production allocation
Production capacity
programming
Replenishment
resource allocation
Safety stock
Safety stocks
stochastic model applications
Supply & demand
Production system
Production management
Inventory control
Replenishment
Resource allocation
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Summary:We consider the problem of allocating production capacity among multiple items, assuming that a fixed proportion of overall capacity can be dedicated exclusively to the production of each item. Given a capacity allocation, production of each item follows a base-stock policy, i.e., each demand triggers a replenishment order to restore safety stocks to target levels. We present procedures for choosing base-stock levels and capacity allocations that are asymptotically optimal. Our objective is to minimize holding and backorder costs, or to minimize holding costs subject to a service-level constraint. Asymptotic optimality refers to large backorder penalties or stringent service-level constraints. Numerical results indicate that our rules perform very well even far from the asymptotic regime. A further approximation step results in allocation rules based on heavy-traffic limits; these, too, perform well.
Bibliography:ObjectType-Article-1
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content type line 14
ISSN:0030-364X
1526-5463
DOI:10.1287/opre.44.5.724