Domicile selection and risk pooling for trucking networks

Abstract

Less-than-TruckLoad (LTL) carriers transport small to medium sized shipments through networks of terminals. One of the issues in designing an LTL network is to determine how drivers should be distributed among locations, with the goal of reducing total variability through risk pooling. By concentrating drivers at a limited number of terminals, the carrier has greater flexibility to respond to random variations in demand, because they can be more readily shifted among routes. The problem is challenging because the risk-pooling objective is concave/minimization, leading to multiple locally optimal solutions. Each solution is defined by a rank ordering of terminals according to assigned demand. When a tour visits multiple terminals, it is assigned to the terminal with the highest rank (i.e., the one with the largest total demand). Based on the rank-ordering concept, a heuristic algorithm and an exact (branch-and-bound) algorithm are developed and applied to test problems. The exact algorithm offers reasonable computation times for moderately sized networks, typical of center-to-center routes of LTL carriers. For large networks, incorporating smaller end-of-line terminals in addition to centers, early termination of the algorithm seems to be a reasonable heuristic.

Enhancing distribution network performance: a quantitative approach to developing a distribution strategy model

“…The higher the CoV, the greater the benefit received from the centralised system, i.e., greater the benefit from risk-pooling (Simchi-Levi et al, 2009). In addition, applying risk-pooling in a transportation network can cause reduced fleet size and number of staff, while increasing utilisation rate in vehicle movements (Hall, 2004). Fritzsche (2012) presented an inventory policy-pooling model, which supports the reduction of total costs and improvement in operational stock planning.…”

Location of cargo terminals in metropolitan areas of developing countries: the Brazilian case

“…The procedures analyzed in studying the optimal location of cargo installations seek to meet various objectives, some of which involve the selection of the best candidate areas (Hall, 2004;Modesti and Sciomachen, 1998); the best place for multimodal terminals (Arnold et al, 2004); and identification of the best size and location of terminals (Taniguchi et al, 2003). According to Sirikijpanichkul and Ferreira (2005), to choose the best location for all interested parties it is very important to understand the ''true'' perception of each agent (for example, trucking companies, users and the community), including strategic individual behavior.…”

Addressing freight imbalance in the truckload trucking industry through hierarchical planning.

“…Although numerous studies have been conducted to demonstrate that driver turnover is excessive and that driver domicile issues are a leading cause, the literature lacks a depth of research related to handling driver domicile problems. Hall (2004), however, provided a significant contribution to domicile theory. His research emphasized the design of longhaul LTL networks and worked on determining how drivers should be distributed among locations.…”

“…Two ofthose times have been in the 4th quarter of2004 (136%) and the 1 st quarter of2005 (120%). The turnover can be partly attributed to driver dissatisfaction (Taylor and Meinert 2000) and due in part to the inability of the truckload carriers to provide regular driving tours (Kutanoglu et al 2001, Hall 2004. With an estimated 403,000 hires per year (Christenson et al 1997), the exorbitant turnover rates cost the truckload trucking approximately between $2.4 billion and $2.8 billion annually (Rodriquez et al 2000).…”

“…Hall (2004), who examined the problem in an LTL network, reports that the most similar topic related to this problem is the "deadhead" problem and that domicile location theory has not been addressed to any significant degree in the transportation literature. Because recruiting new drivers from specific domiciles could not be immediately put in practice due to a carrier's existing driver workforce, this scenario represents a problem that addresses freight imbalance through tactical planning.…”