Search arXivSearch

arXiv · 2506.10290

Dynamic Less-Than-Truckload Transportation Planning in Hyperconnected Hub Networks with Multi-Carrier Operations

Abstract

Less-than-truckload (LTL) shipment is vital in modern freight transportation yet is in dire need of more efficient usage of resources, higher service responsiveness and velocity, lower overall shipping cost across all parties, and better quality of life for the drivers. The industry is currently highly fragmented, with numerous small to medium-sized LTL carriers typically operating within dedicated regions or corridors, mostly disconnected from each other. This paper investigates the large-scale interconnection of LTL carriers enabling each to leverage multi-carrier networks for cross-region services exploiting their mutual logistic hubs, in line with Physical Internet principles. In such a network, efficient open cooperation strategies are critical for optimizing multiparty relay shipment consolidation and delivery, transport and logistic operations and orchestration, and enabling inter-hub driver short hauls. To dynamically plan relay truck transportation of involved carriers across hyperconnected hub networks, we develop an optimization-based model to build loads, coordinate shipments, and synchronize driver deliveries. We report a simulation-based experiment in a multiparty LTL network covering the eastern U.S. in three scenarios: 1) each carrier operates separately and serves its clients with end-to-end transportation, 2) each carrier operates separately and adopts relay transportation in its service region, and 3) all carriers operate jointly and serve clients in the multi-carrier hyperconnected relay network. By comparing these three scenarios, we evaluate the impact of relay transportation and carrier cooperations on cost savings, trip duration, and greenhouse gas emissions. Overall, this research advances operational efficiencies through an effective collaborative solution across the LTL industry and contributes to the pursuit of sustainable logistics networks.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tiankuo Zhang, Jingze Li, Benoit Montreuil. 2025-06-12. Dynamic Less-Than-Truckload Transportation Planning in Hyperconnected Hub Networks with Multi-Carrier Operations. https://arxiv.org/abs/2506.10290

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The Riemannian Convex Bundle Method

We introduce the convex bundle method to solve convex, non-smooth optimization problems on Riemannian manifolds of bounded sectional curvature. Each step of our method is based on a model that involves the convex hull of previously collected subgradients, parallelly transported into the current serious iterate. This approach generalizes the dual form of classical bundle subproblems in Euclidean space. We prove that, under mild conditions, the convex bundle method converges to a minimizer. Several numerical examples implemented using Manopt$.$jl illustrate the performance of the proposed method and compare it to the subgradient method, the cyclic proximal point algorithm, as well as the proximal bundle method.

math.OC

Omega-Limit Sets and Input-to-State Stability in Power Grids With Switching Equilibria

This paper studies a power transmission system with both conventional generators (CGs) and distributed energy assets (DEAs) providing frequency control. We consider an operating condition with demand aggregating two dynamic components: one that switches between different values on a finite set, and one that varies smoothly over time. Such dynamic operating conditions may result from protection scheme activations, external cyber-attacks, or due to the integration of dynamic loads, such as data centers. Mathematically, the dynamics of the resulting system are captured by a system that switches between a finite number of vector fields -- or modes--, with each mode having a distinct equilibrium point induced by the demand aggregation. To analyze the stability properties of the resulting switching system, we leverage tools from hybrid dynamic inclusions and the concept of $Ω$-limit sets from sets. Specifically, we characterize a compact set that is semi-globally practically asymptotically stable under the assumption that the switching frequency and load variation rate are sufficiently slow. For arbitrarily fast variations of the load, we use a level-set argument with multiple Lyapunov functions to establish input-to-state stability of a larger set and with respect to the rate of change of the loads. The theoretical results are illustrated via numerical simulations on the IEEE 39-bus test system.

math.OC

Cellular flow control design for mixing based on the least action principle

We consider a novel approach for the enhancement of fluid mixing via pure stirring strategies building upon the Least Action Principle (LAP) for incompressible flows. The LAP is formally analogous to the Benamou--Brenier formulation of optimal transport, but imposes an incompressibility constraint. Our objective is to find a velocity field, generated by Hamiltonian flows, that minimizes the kinetic energy while ensuring that the initial scalar distribution reaches a prescribed degree of mixedness by a finite time. This formulation leads to a ``point-to-set" type of optimization problem which relaxes the requirement on controllability of the system compared to the classic LAP framework. In particular, we assume that the velocity field is induced by a finite set of cellular flows that can be controlled in time. To establish finite time feasibility, we introduce an operator-theoretic switching argument that combines the long-time cellular flow mixing result with the von Neumann alternating-projection theorem. We then leverage the direct method to establish the existence of an optimal solution. Finally, we derive the corresponding optimality conditions for the time-dependent control problem and conduct numerical experiments demonstrating the effectiveness of the proposed control design.

math.OC