Analysis of demand variability and robustness in strategic transportation planning

Creation of a long-term strategic transportation plan is critical for companies in order to make informed decisions about fleet capacity, number of drivers needed, fleet allocation to domiciles, etc. However, the inherent demand variability present on a transportation network, in terms of weekly occurrences of lane volume, results in emergency weekly shipments that deviate from the long-term plan. This leads to a sub-optimal weekly execution, resulting in higher overall costs, compared to initial projections. Hence, it is important to address this variability while creating a strategic plan, such that it is robust enough to handle these variations, and is easy to execute at the same time. The purpose of this thesis is to create a stochastic annual plan using linear programming techniques for addressing demand variability, and prove its robustness using simple heuristics, so that it is easy to execute at an operational level. Through the use of simulations, it is shown that the proposed planning methodology is within 6% of the optimal solution costs and handles 71% of the demand variability occurring on a weekly basis, making it easy for operational managers to execute. Thus, the proposed plan reduces the optimality gap between long-term planning and weekly operations, creating a tighter bound over the projected versus actual costs incurred, which helps develop a better transportation strategy.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Lokhandwala, Ahmedali (Ahmedali Abbas)

Advisor dc:contributor.advisor

• Chris Caplice.

• Engineering Systems Division.
• Civil and Environmental Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/61003

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/61003