| Article ID: | iaor2009227 |
| Country: | Netherlands |
| Volume: | 59 |
| Issue: | 1 |
| Start Page Number: | 2 |
| End Page Number: | 12 |
| Publication Date: | Jan 2008 |
| Journal: | Journal of the Operational Research Society |
| Authors: | Mitra G., Lucas C., Poojari C.A. |
| Keywords: | supply & supply chains, programming: integer, heuristics: genetic algorithms, programming: probabilistic, simulation: applications |
We consider a strategic supply chain planning problem formulated as a two-stage stochastic integer programming (SIP) model. The strategic decisions include site locations, choices of production, packing and distribution lines, and the capacity increment or decrement policies. The SIP model provides a practical representation of real-world discrete resource allocation problems in the presence of future uncertainties which arise due to changes in the business and economic environment. Such models that consider the future scenarios (along with their respective probabilities) not only identify optimal plans for each scenario, but also determine a hedged strategy for all the scenarios.