A time–space scheduling model for optimizing recurring bulk railcar deliveries

Abstract

This work presents a time–space network flow model for scheduling recurring bulk rail deliveries from suppliers to customers. The objective is to maximize demand satisfied while minimizing waiting times for loading and unloading the bulk commodity. The model uses a variety of information including customer demand, rail network characteristics, loading and unloading hours, and track and station capacities. The planning horizon length and planning period can be varied to provide solutions for both long term planning and short term daily operations. The paper includes computational studies that examine the tradeoff between planning period length and schedule quality.