Conceptual Design and Analysis of Rail Car Unloading Area

Abstract

Faced with growing demand at their Alexandria, Louisiana laundry detergent plant, Procter & Gamble asked a design team from the University of Texas to undertake a study of the raw materials unloading area. This chapter reports on the results of that effort and presents the accompanying mathematical model developed to help analyze the material flows. In the first part of the study the design team established daily requirements for the number of raw material rail cars unloaded per day. The related combinatorial optimization problem of assigning rail cars to positions on the platform and unloading equipment to rail cars, was modeled as a mixed integer nonlinear program. The inability of two standard commercial codes to find optimal solutions led to the development of a greedy randomized adaptive search procedure (GRASP). Accounting for the operational and physical limitations of the system, the GRASP was used to determine the maximum performance that could be achieved under normal conditions. The second part of the study called for the conceptualization of alternative designs for meeting an expected 14% increase in demand over the next few years. The analytic hierarchy process in conjunction with a standard scoring model was used to rank the evaluation criteria and to select the most preferred alternative. A worst case analysis of the top candidate confirmed its performance capabilities.