Date on Master's Thesis/Doctoral Dissertation
12-2007
Document Type
Master's Thesis
Degree Name
M.S.
Department
Industrial Engineering
Committee Chair
Heragu, Sunderesh S.
Subject
General Electric Company; Shipping--Management
Abstract
The Consumer and Industrial group of the General Electric Company (GE) allocates its shipping truckload to seventeen different trucking companies over 701 different routes from each of its nine terminals to 48 contiguous states. One of the seventeen trucking companies is its wholly owned subsidiary, which is PDCO. All of the others are contract-based trucking companies. GE Consumer and Industrial managers realized that they were not allocating the entire trucking capacity in an optimal fashion to the seventeen trucking companies, and the spreadsheet-based analytical tool used on a daily basis could not generate an optimal or near optimal solution. They asked University of Louisville to help solve their distribution problem based on quantitative analysis. Several linear programming models were developed to help the management of the Consumer and Industrial group develop optimal solutions. Results from one of the models (the most realistic one) indicate that GE Consumer and Industrial could save approximately 15.59% of its shipping cost through an optimal re-allocation of its trucking workload to the seventeen trucking companies. This model also increases PDCO business by 28.92% compared to the current solution. This increase in capacity exceeds those of two current largest competitors. Two user-friendly tools were also developed for long-term daily use by the managers. The interface program tool is to query the solutions given by the optimization models. The tool allows us to manage all the data easily and quickly. The Excel file tool allows managers to assign trucking volume to each company lane by lane. It also provides additional information based on new assignment, such as total cost, trips for each trucking company and cost for operating one route.
Recommended Citation
Yang, Xu 1983-, "Optimal allocation of trucking workload at GE Consumer and Industrial." (2007). Electronic Theses and Dissertations. Paper 1619.
https://doi.org/10.18297/etd/1619
