Background: Truck scheduling at cross-docking terminals has received much academic attention over the last three decades. A vast number of mixed-integer programming models have been proposed to assign trucks to dock-doors and time slots. Surprisingly, only a few models assume fixed outbound truck departures that are often applied in the less-than-truckload or small parcel and express delivery industry. To the best of our knowledge, none of these papers explore whether a discrete-time or continuous-time model formulation has a better computational performance. This paper attempts to close this research gap and tries to shed light on which type of formulation is advantageous. Therefore, a variant of the truck scheduling problem with fixed outbound departures is considered. This problem's objective is to find a feasible truck schedule that minimizes the number of delayed freight units. Methods: We propose two model formulations for the described variant of the truck scheduling problem with fixed outbound departures. Specifically, the problem is formulated as a discrete-time and a continuous-time mixed-integer programming model. Results: A computational experiment is conducted in order to assess the computational performance of the presented model formulations. We compare the discrete-time and continuous-time formulation in terms of both the solution quality and computational time. Conclusions: The computational results show that the proposed discrete-time model formulation can solve problem instances of medium size to proven optimality within less than one minute. The continuous-time model formulation, on the other hand, can solve small instances to optimality. However, it requires longer solution times than the discrete-time formulation. Furthermore, it is unable to solve medium-sized instances within a 5-minute time limit. Thus, it can be summarized that the proposed discrete-time model formulation is clearly superior to the continuous-time model formulation.

Truck scheduling, which assigns a dock-door and a processing interval to each inbound and outbound truck, is an essential operational decision problem in cross-docking platforms and distribution centers. It has attracted considerable academic attention. Most studies, however, have neglected internal resources (e.g., workers or material handling equipment) and hence failed to address two major concerns of cross docking practitioners: (i) determining the number of resources needed, and (ii) scheduling the internal resources in an efficient way. This study sets out to examine the value of utilizing the internal resource requirements as the main performance metrics in truck scheduling. The problem considered in this paper is how to schedule a set of inbound trucks with time windows at a multidoor cross-docking platform, where the departure times of outbound trucks follow a given schedule. The goal is to identify a feasible truck schedule that can be executed with a minimum number of internal resources. For this setting, a mixed-integer programming model is proposed. Furthermore, a column generation-based solution procedure is developed. We show that by using the internal resource requirements as the main performance measure, the operational efficiency of the cross-docking platform can be significantly increased. It also helps to avoid large peak workloads and leads to level truck schedules with superior resource utilization levels. Computational experiments show that the proposed heuristic algorithm can obtain high-quality solutions for very large problem instances within a short computation time. Due to its tight lower bound, the solution procedure can even prove optimality for most problem instances. (c) 2021 Elsevier Ltd. All rights reserved.

China's courier/express/parcel (CEP) sector has experienced high growth rates in the past decade, which puts high pressure on the equipment of CEP providers, particularly transshipment hubs. Automation is considered a key enabler to improve efficiency. In this context, we conducted a research project about transshipment hub automation, the suitability of automation equipment, and automation strategies in China's CEP sector. Assessments from 12 experts working in leading functions at CEP service providers and equipment providers in China were collected during the period of 2016 and 2018. We identified automation equipment for various hub process steps, assessed the suitability of automation equipment, and identified both automation motives and barriers. Our findings indicate that mainly due to missing process standards and the required investment for automation, the degree of transshipment hub automation in China's CEP sector is currently rather low.

In this paper a model for negotiation support in tactical procurement planning is designed, which is based on a real planning problem from the liquid gas trade sector. The problem is modeled as an assignment problem and transformed into a robust form. Computational experiments using data from a practice partner are presented to demonstrate the effective decision support of our approach.