Scalable Approaches to Time-Dependent Path and Routing Problems
Author(s)
He, Edward Yuhang
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Abstract
Many combinatorial optimization problems involve an aspect of time, whether due to changing conditions, updated information, or being under a continuous decision-making process. A popular domain for time-based decision making is logistics, where it is not only important to decide along which routes products need to be transported, but also when the transportation should occur. The timing for these problems is critical to take advantage of changing operational conditions such as traffic, capacity, and costs. Unfortunately, introducing time as an additional dimension significantly increases the size of models over their static counterparts. In fact, solving such models is often done via heuristics as existing solution methods are computationally intractable. This dissertation aims to provide insights into how scalable solution methodologies can be developed for such problems in path and routing problems.
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Date
2021-07-07
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Text
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Dissertation