| Abstract
| - A new modeling framework for multiperiod supply chain planning problems is proposed in this paper. Theproblem is transformed into a set of two optimization problems. At first, demands in distinctive geographicallocations over multiple time periods are aggregated and distributed to multiple entities using an operationpolicy that was employed by Ryu and Pistikopoulos (Ind. Eng. Chem. Res.2005, 44, 2174). Individual single-site multiperiod planning problems are then constructed based on their allocated demands. These optimizationproblems are mathematically formulated as mixed-integer linear programming (MILP) problems andnumerically demonstrated with two examples. From the results of the examples, it is seen that the key issuein the multiperiod supply chain planning problem is the distribution of multiple demands to multiple entities.
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