Title
Revisiting order assignment problems in a real-case vehicle compound scenario
Abstract
With rising transshipment volumes, new challenges arise for vehicle transshipment compounds: They have to facilitate the complex logistics processes of intermodal transports of vehicles on their compounds with ever shorter loading and unloading times of ships and trains in order to satisfy external stake holders. In addition, customised services for vehicles offered by the compound operator cause inter-terminal transport (ITT). All transports of vehicles have to be carried out by human workers who drive the vehicles from one location to the next. Usually, the drivers are transported across the compound by shuttles and therefore grouped together in teams. Accordingly, the drivers are modelled in cohorts but not individually. In this paper, we set up a model with a control algorithm that handles each driver individually. New orders are assigned to each driver based on their current location. By doing so, we allow for the possibility to individually assign orders that are within walking distance so that shuttle rides and associated waiting times can be avoided. Shuttles are still available for longer distances. We state the problem as an assignment problem to find the time-minimising combination of drivers, shuttles and orders. The proposed control algorithm includes the actual states of drivers, shuttles and available orders as a feedback control. It is carried out in a rolling planning horizon manner to periodically obtain a new solution based on the actual state of the compound. We verify the proposed control algorithm and conduct simulations with two variants of the algorithm which differ in terms of shuttle routing. The results show that the proposed model and control algorithm are suitable to simulate order assignments in a real-case vehicle compound scenario. Moreover, including the possibility to reach orders by walking offers large potential for the productivity on vehicle compounds.
Year
DOI
Venue
2021
10.1109/CiSt49399.2021.9357210
2020 6th IEEE Congress on Information Science and Technology (CiSt)
Keywords
DocType
ISSN
assignment problem,optimisation,simulation,model predictive control
Conference
2327-185X
ISBN
Citations 
PageRank 
978-1-7281-6647-6
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Marit Hoff-Hoffmeyer-Zlotnik100.34
Tobias Sprodowski202.37
Michael Freitag300.34