Optimization Models for Locating Cross-docks under Capacity Uncertainty

The objective of this thesis is to develop mathematical models for locating cross-docks in a supply chain. Cross-docking is a strategy which can help consolidate the goods in the supply chain and save costs by reducing the number of truck trips. In this thesis four optimization models were developed. First two optimization models termed Model A and Model B were deterministic models. The goal of model A was to choose exactly P locations to locate cross-docks so that the transportation and handling costs are minimized. The goal of model B is to locate as many cross-docks as needed so that total routing, handling, and facility location costs are minimized. Then we developed a chance constraint model and a recourse model which accounted for capacity uncertainties at cross-dock location. The chance constraint model accounts for day to day operational uncertainties whereas the recourse model accounts to drastic reductions in capacities due to disruptions. Extensive computational analysis was conducted on two networks with parameters consistent with real world freight operations. The results reveal that cross-docking provides significant savings when the demand sizes are small and there is more potential for consolidation. For larger demands where the potential for consolidation is less, cross-dock savings diminish. The results were found to be consistent across a variety of capacity uncertainty scenarios.

Name thesis:degree_name

MS

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Civil and Environmental Engineering

Year dc:date.available

2012

Author dc:creator

• Soanpet, Anshul

Contributors dc:contributor

• Avinash Unnikrishnan
• David R. Martinelli
• Radhey Sharma

• Civil engineering

Identifier

https://researchrepository.wvu.edu/etd/582

OAI identifier oai:identifier

oai:researchrepository.wvu.edu:etd-1585