A Mathematical Programming Model for Matching Sequential Activities in Logistics Systems with Tolerance for Erroneous or Missing Data

摘要

We present a mathematical programming model that was constructed to match flight data from the FAA Air Traffic Control system with airline gate data maintained by an individual carrier. The purpose is to provide reliable data for calibrating realistic models of airport activity. Our technique also has potential value for other logistics and information systems where time stamps for sequential stages in a process are blended to impute time durations for activities, especially where observations are occasionally missing or imperfectly recorded.