A Centralized Time-Dependent Multiple Carrier Collaboration Problem for Less-than-Truckload Carriers;

摘要

This paper addresses a time-dependent centralized multiple carrier collaboration problem (TD4MCCP) for the small- to medium-sized less-than-truckload (LTL) industry. The TD-MCCPrepresents a collaborative strategy in which a central entity (such as a 3PL firm) seeks tominimize the total system costs of an LTL carrier collaborative consisting of multiplecollaborating carriers, by identifying collaborative opportunities over a shared network underthree rate-setting behavioral strategies and a leasing alternative. In contrast to conventional time9dependent network problems that typically view demand as dynamic, in the proposed LTLmultiple carrier collaboration framework, capacities are time-dependent but known a priori, anddemand is fixed. The TD-MCCP is modeled as a binary (0-1) multi-commodity minimum costflow problem formulation for two rate-setting behavioral cases and solved using a branch-and13cut algorithm. The first case studies the effect of a single rate behavioral strategy at a time, andthe second case studies the effect of multiple rate behavioral strategies simultaneously.Numerical experiments are conducted to seek insights on the computational performance of theTD-MCCP formulations under various network sizes and number of shipments. The resultsindicate that the attractiveness of the time-dependent multiple carrier collaboration paradigmincreases with a volume-oriented rate-setting strategy. Also, a volume-oriented rate strategy hasthe potential to increase the capacity utilization of carriers seeking to minimize empty-haul trips.Finally, the leasing alternative can serve as a viable option for a centralized collaborative system,especially when affordable collaborative capacity is scarce.