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 Decision-Maker’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.
Supply Chain Management through the Stochastic Goal Programming Model
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