TY - GEN
T1 - Vertical Stability Constraints in Combined Vehicle Routing and 3D Container Loading Problems
AU - Krebs, Corinna
AU - Ehmke, Jan Fabian
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021
Y1 - 2021
N2 - The vertical stability of the cargo is one of the most important loading constraints, since it ensures parcels from falling on the ground. However, frequently considered constraints either lead to unstable positions, are too restrictive or have high complexity. This paper focuses on the evaluation of different vertical stability constraints, analyses corner cases and introduces a new improved constraint. For the first time, constraints based on the science of statics are considered in the context of combined Capacitated Vehicle Routing Problem with Time Windows and 3D Loading (3L-VRPTW). All constraints are embedded in an established hybrid heuristic approach, where an outer Adaptive Large Neighbourhood Search tackles the routing problem and an inner Deepest-Bottom-Left-Fill algorithm solves the packing problem. For the computational tests, we use a well-known instance set enabling a comparison w.r.t. the number of customers, the number of items and the number of item types. Based on the impact on the objective values and on the performance, we give recommendations for future work.
AB - The vertical stability of the cargo is one of the most important loading constraints, since it ensures parcels from falling on the ground. However, frequently considered constraints either lead to unstable positions, are too restrictive or have high complexity. This paper focuses on the evaluation of different vertical stability constraints, analyses corner cases and introduces a new improved constraint. For the first time, constraints based on the science of statics are considered in the context of combined Capacitated Vehicle Routing Problem with Time Windows and 3D Loading (3L-VRPTW). All constraints are embedded in an established hybrid heuristic approach, where an outer Adaptive Large Neighbourhood Search tackles the routing problem and an inner Deepest-Bottom-Left-Fill algorithm solves the packing problem. For the computational tests, we use a well-known instance set enabling a comparison w.r.t. the number of customers, the number of items and the number of item types. Based on the impact on the objective values and on the performance, we give recommendations for future work.
KW - 3D loading
KW - Vehicle Routing Problem
KW - Vertical stability
UR - http://www.scopus.com/inward/record.url?scp=85116352751&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-87672-2_29
DO - 10.1007/978-3-030-87672-2_29
M3 - Contribution to proceedings
AN - SCOPUS:85116352751
SN - 9783030876715
T3 - Lecture Notes in Computer Science
SP - 442
EP - 455
BT - Computational Logistics - 12th International Conference, ICCL 2021, Proceedings
A2 - Mes, Martijn
A2 - Lalla-Ruiz, Eduardo
A2 - Voß, Stefan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 12th International Conference on Computational Logistics, ICCL 2021
Y2 - 27 September 2021 through 29 September 2021
ER -