Coordinated Contract Decisions in a Make-to-Order Manufacturing Supply Chain: A Stochastic Programming Approach

One of the important objectives of supply chain S&OP (Sales and Operations Planning) is the profitable alignment of customer demand with supply chain capabilities through the coordinated planning of sales, production, distribution, and procurement. In the make‐to‐order manufacturing context cons...

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Bibliographic Details
Published in:Production and operations management Vol. 22; no. 3; pp. 642 - 660
Main Authors: Feng, Yan, Martel, Alain, D'Amours, Sophie, Beauregard, Robert
Format: Journal Article
Language:English
Published: Los Angeles, CA Blackwell Publishing Ltd 01.05.2013
SAGE Publications
Blackwell Publishers Inc
Subjects:
contract design
Decision making models
Integer programming
make-to-order manufacturing
Manufacturing
Operations management
Planning
Sales forecasting
sample average approximation
stochastic programming
Studies
Supply & demand
supply chain coordination
Supply chain management
Supply chains
contract design
supply chain coordination
make‐to‐order manufacturing
sample average approximation
stochastic programming
ISSN:1059-1478, 1937-5956
Online Access:Get full text
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Summary:One of the important objectives of supply chain S&OP (Sales and Operations Planning) is the profitable alignment of customer demand with supply chain capabilities through the coordinated planning of sales, production, distribution, and procurement. In the make‐to‐order manufacturing context considered in this paper, sales plans cover both contract and spot sales, and procurement plans require the selection of supplier contracts. S&OP decisions also involve the allocation of capacity to support sales plans. This article studies the coordinated contract selection and capacity allocation problem, in a three‐tier manufacturing supply chain, with the objective to maximize the manufacturer's profitability. Using a modeling approach based on stochastic programming with recourse, we show how these S&OP decisions can be made taking into account economic, market, supply, and system uncertainties. The research is based on a real business case in the Oriented Strand Board (OSB) industry. The computational results show that the proposed approach provides realistic and robust solutions. For the case considered, the planning method elaborated yields significant performance improvements over the solutions obtained from the mixed integer programming model previously suggested for S&OP.
Bibliography:istex:2A0E5F94102F66152705EB6631EA060866256DA8
NSERC - No. CAP 248987-01
ark:/67375/WNG-B215H366-N
ArticleID:POMS1385
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:1059-1478
1937-5956
DOI:10.1111/j.1937-5956.2012.01385.x