United States Department of Transportation
i
Continuous Approximation Models with Temporal Constraints and Objectives [Research Brief]
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2023-09-01
[PDF-267.77 KB]
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Abstract:The purpose of this project was to discover new continuous approximation models for modern logistical problems in which time plays a significant role, with a specific focus on last-mile delivery. Famous examples of such problems include the vehicle routing problem with time windows (VRPTW) and the cumulative travelling salesperson problem (CTSP). The continuous approximation paradigm is a quantitative method for solving logistics problems in which one uses a small set of parameters to model a complex system, which results in simple algebraic equations that are easier to manage than (for example) large-scale optimization models. As a further benefit, one often obtains insights from these simpler formulations that help to determine what affects the outcome most significantly. Although continuous approximation models have been used for over 60 years in logistics systems analysis, there has been very little research conducted on their use to problems with temporal features such as those described above. To the best of our knowledge, this project was the first of its kind to incorporate these temporal features into the continuous approximation paradigm.
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