Supply chain management through the stochastic goal programming model

Supply chain (SC) design problems are often characterized with uncertainty related to the decision-making parameters. The stochastic goal programming (SGP) was one of the aggregating procedures proposed to solve the SC problems. However, the SGP does not integrate explicitly the Manager’s preference...

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Bibliographic Details
Published in:Annals of operations research 2017-04, Vol.251 (1-2), p.351-365
Main Authors: Azimian, Alireza, Aouni, Belaid
Format: Article
Language:English
Subjects:
Algorithms
Business and Management
Collaboration
Combinatorics
Decision analysis
Decision making
Design parameters
Goal programming
Inventory
Linear programming
Literature reviews
Manufacturing
Mathematical models
Mathematical programming
Normal distribution
Operations research
Operations Research/Decision Theory
Optimization
Parameter uncertainty
Programming
Random variables
Stochasticity
Studies
Suppliers
Supply chain management
Supply chains
Theory of Computation
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Summary:Supply chain (SC) design problems are often characterized with uncertainty related to the decision-making parameters. The stochastic goal programming (SGP) was one of the aggregating procedures proposed to solve the SC problems. However, the SGP does not integrate explicitly the Manager’s preferences. The aim of this paper is to utilize the chance constrained programming and the satisfaction function concept to formulate strategic and tactical decisions within the SC while demand, supply and total cost are random variables.
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-015-2007-1