We present a Lagrangean-based decomposition that is used to generate solutions for an integrated production and transportation planning problem in a two-stage supply chain. This supply chain consists of a number of facilities, each capable of producing the final products, and a number of retailers. It is assumed that the retailers' demands are known and deterministic, and that there are production capacity constraints. The problem is formulated as a multi-commodity network flow problem with fixed charge costs which is a NP-hard problem. An alternative formulation is provided whose linear programming relaxation gives tighter lower bounds. The quality of the lower and upper bounds from the Lagrangean decomposition is tested on a large set of randomly generated problems.
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