Mathematical Programming Models and Algorithms for Large-Scale Problems in Transportation and Logistics

The research effort presented in this document focuses on the application of optimizationmethods to solve two real world problems in the logistics and transportation industry. Thefirst essay looks at the problem of assigning package destinations to secondary sorterswithin an automated sorting facility, in a way that balances the workload, while explicitlyaccounting for day-to-day fluctuation in package volumes and adhering to the outboundloading capacities of the workcenters in the facility. In the second essay we develop thetheory needed for solving the Resource Constrained Elementary Shortest Path Problem(RCESPP) while accounting for idle time costing. This problem arises as the subproblem forgenerating columns which, in our case, correspond to feasible routes in a large scale routingproblem that accounts for deliveries followed by pickups and that penalizes idle time. Finally,in the third essay we consider the problem of optimizing the daily store servicing routes formajor grocery chains, while using real data from a well known chain. We propose to framethe problem as a Capacitated Vehicle Routing Problem with Time Windows that accountsnot only for the minimization of travelling costs, but also the minimization of idle timecosts. Given the nature of the problem, we propose a reformulation using decompositiontechniques which we intend to solve under a customized column generation setup, consistingof several phases.

Author

• Novoa, Luis Jose

Language

• en

Keyword

• Optimization
• Routing
• Nonlinear models
• Transportation
• Labeling Algorithms

Date created

• 2016

Type of Work

• Dissertation

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Decision Sciences

Degree

• Ph.D.

Advisor

• Jarrah, Ahmad I

Committee Member(s)

• Prasad, Srinivas
• Morton, David P
• Ball, Michael O
• Soyer, Refik

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/7w62f837g