An Improved Freight Transportation Planning System for Less‐Than‐Truckload Operations of a Third‐Party Logistics Carrier

ABSTRACT Less‐than‐truckload (LTL) transportation is a widely used shipping modality within the logistics industry, facilitating the movement of loads insufficient in size to occupy the entirety of a truck's capacity. Drawing on the real‐life problem of a third‐party logistics (3PL) carrier, which navigates an expansive transportation network and unpredictable demand patterns, we propose a centralized planning approach for LTL transportation, taking advantage of consolidation opportunities at cross‐dock hubs to minimize long‐term freight costs while ensuring on‐time delivery. We present an integer linear programming (ILP) formulation to generate a multi‐day plan with known demands and a daily planning problem (DPP) model to be solved daily, emulating the available order information in a real planning scenario. DPP optimizes truck routes and loading plans, incorporating a penalty cost for postponed transportation requests. We devise a novel multi‐stage matheuristic integrating geographical decomposition with tractable integer programming models and column generation‐based heuristics. With this approach, the DPP is solved in fewer than 2 h of run‐time for real problem instances with as high as 1400 transportation orders. We benchmark our results against a baseline heuristic that mirrors the firm's existing planning approach through a multi‐period simulation. Our comparative evaluations reveal a noteworthy 7.8% improvement in long‐term freight costs, concurrently maintaining adherence to the 98% on‐time delivery target.