Multi-disruption resilient hub location–allocation network design for less-than-truckload logistics

<div> <div> <div>Less-than-truckload (LTL) logistics presents an interesting and often overlooked practice area of hub location–allocation problems, with its variable discount rates playing a game-changing role. Vulnerability of the roads is another critical factor that has often been neglected when designing hub networks. In this paper, a novel integrated model is designed to solve the LTL hub network design problem, incorporating a practical stepwise discount function. The proposed model is further extended to a reliability-oriented version that can resiliently withstand multiple, simultaneous road disruptions. We use the <a title="Learn more about failure mode and effect analysis from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/engineering/failure-modes-and-effects-analysis">failure mode and effect analysis</a> (FMEA) technique to encompass the likelihood of experiencing each failure mode, together with the monetary and service-level effects. Coupled with probability theory, it leads to the introduction of a novel <a title="Learn more about closed form from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/engineering/closed-form">closed form</a> for <a title="Learn more about serviceability from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/engineering/serviceability">serviceability</a> under multiple concurrent failures. Having such a function enables us to deploy exact optimization methods. Given the natural complexity of the problem, we also present effective linearization approaches. Numerical benchmarks demonstrate the superiority of the novel reliability-oriented approach over the basic version, successfully realizing desired serviceability levels as high as 80%. It also benefits from avoiding unnecessary rerouting, making it even more attractive for policymakers to design efficiently resilient transportation networks, especially if low-range, zero-emission trucks are incorporated.</div> </div> </div> <div></div>