Chemical supply chain networks provide large opportunities for cost reductions through the redesign of the flow of material from producer to customer. In this paper we present a mixed-integer linear program (MILP) capable of optimizing a multi-product supply chain network made up of production sites. an arbitrary number of echelons of distribution centers, and customer sites. The emphasis of our approach is on the redesign of existing supply chain networks. The model does not lump customer demand into zones. but rather deals with individual customer demand to directly address customer preferred mode of transport at each location. Historical records can be used to fix decision variables in the model so that a base case can be computed to validate the model and contrast it against the optimized network. The details inherent in this approach allow the optimization results to be partitioned and prioritized for implementation. The model results are processed to assign cost components to individual customer records. A simple case study is presented to illustrate the method and actual industrial results are reviewed. (c) 2007 Elsevier Ltd. All rights reserved.