Heavy Haul Corridor Selection and Service Design Models

Abstract

Heavy haul corridors are capital intensive and are relatively expensive to maintain. It is therefore imperative that heavy haul corridors are chosen with care, such that sufficient traffic is available on the corridors to ensure adequate returns. The strategic choice will be dictated by projected pattern and volume of freight traffic, projected pattern of passenger traffic and terminal facilities. Various choices may be obtained with different rolling stock and locomotive capacity to obtain scenarios with existing and future fleet characteristics, as well as future terminal facilities. Further, tactical operating plans for networks with heavy haul corridors should be designed properly to ensure maximum utilization of such corridors with a given set of customer demands, rolling stock and locomotive size and capacity, terminal facilities and capacity of peripheral networks. Such operating plans which might span from a fortnight to three months, include decisions regarding routes, frequency of services, aggregation and disaggregation policies, empties repositioning policies and direct or consolidating train service policies. These operating plans may also depend on the service level committed to a customer, which is again tied to a particular pricing. This paper proposes two operations research based models: (i) a model for choosing a heavy haul corridor(s) within an existing network and (ii) a model for design of an optimal operating plan for an existing network with a designated heavy haul corridor(s). The models are further demonstrated on a hypothetical railroad network with test data. The contributions of the proposed models are manifold, few of which are: scenario analysis with various combinations of demand patterns, fleet size and characteristics and terminal facilities; enabling investment decisions for up gradation of track, fleet or terminal facilities through comparative analysis of scenarios; and enabling service design to meet specific customer needs.