Spring, 2024
Davod Hosseini is a good guy to know if you’re a commuter. That’s because his “operations research” or OR, tries to solve complex problems in transportation planning and logistical management.
“The core process of OR involves identifying an issue, formulating a mathematical model to represent it, gathering and analyzing relevant data to understand its behaviour, and, finally, providing actionable recommendations by finding optimal or near-optimal solutions,” explains Hosseini, assistant professor of management science at Saint Mary’s University’s Sobey School of Business.
Specifically, Hosseini leverages OR to optimize routing, scheduling and vehicle assignment in two types of transportation systems — regular systems, in which he looks at transportation costs and customer satisfaction, and in riskier transportation systems involving transportation of hazardous materials (hazmat) via railroads, in which he aims to minimize risk.
“The optimization process in both cases is performed by considering factors such as traffic patterns, distance, service and delivery times, demand forecast and vehicle capacity, while ensuring all operational constraints, government regulations and customer requests are fulfilled,” Hosseini says. “However, the inherent variability in these factors adds a layer of complexity to the model, making it more challenging to achieve an optimal solution.”
“Companies such as Amazon or FedEx leverage advanced route optimization to plan daily deliveries for thousands of packages,” Hosseini explains. “The system considers factors such as delivery windows, traffic conditions, package size and driver location to create efficient routes and meet tight delivery deadlines.”
Another application is home health-care, where providers visit multiple patients daily. The system can account for patient location, appointment times, last-minute appointment cancellations, new patient requests, care urgency and unexpected traffic delays, to name a few, and then generate route planning that minimizes travel time, ensures on-time visits and maximizes patient experience.
On the hazmat side, one could imagine a use for chemical manufacturers who want to transport their products by rail. The software considers such factors as population density along the route and prioritizes less populated routes in case of an accident, weather conditions and track maintenance.
Hosseini says he uses ACENET services because he usually has large datasets, numerous constraints and variables in the mathematical model, and complex optimization algorithms.
“Traditional computing can become slow and impractical when dealing with vast amounts of data, such as railroad networks with thousands of tracks and intersections or logistics scenarios involving millions of delivery points. HPC provides the processing power to handle these large datasets efficiently.”
He says he has benefited from ACENET staff’s expertise in supercomputing to migrate his workflows from his university desktop to an HPC cluster.
Without ACENET’s tools, Hosseini says his work would take weeks or months to complete.
