Moraga, Reinaldo J.
M.S. (Master of Science)
Department of Industrial and Systems Engineering
Inclement weather has a visceral impact on transportation systems, but it has been made undeniably clear. Reliable ground transportation is absolutely fundamental in global logistics, and the need to deliver goods to customers in a timely manner has never been more important. The field of operations research offers some quality logistics problems with the foresight to provide efficient transportation solutions. One of the most prevalent problems in operations research is the Traveling Salesman Problem (TSP). Although much research has gone into solving the classic TSP and some of its variants, none have been truly dedicated to integrating meteorological sciences.
The methodological framework uses roadway travel distances as edges in a TSP network of real cities. Those edges must be transformed by some reduced travel speed, which becomes a function of both the static distance and dynamically probabilistic weather phenomena. A uniform speed is given to form control solutions for driving in ideal conditions. Upper and lower bounds for travel speeds in inclement weather are used to non-uniformly penalize the edges, and the TSP is resolved again. Both a greedy nearest neighbor heuristic and a simulated annealing heuristic are used for control and both bounded solutions. As expected, simulated annealing outperformed nearest neighbor in all cases. Expected locally optimal tour times were significantly shorter for the control solutions, while the longest locally optimal tours were found during most problematic and most probabilistic driving conditions. Although seemingly trivial, these results show how weather science and operations research can be sewn together in the name of transportation safety and efficiency.
Wright, Andrew, "Driving Under Weather: An Exploration of the Traveling Salesman Problem with Probabilistic Unfavorable Driving Conditions" (2018). Graduate Research Theses & Dissertations. 7791.
Northern Illinois University
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