Details
| Original language | English |
|---|---|
| Pages (from-to) | 325-357 |
| Number of pages | 33 |
| Journal | OR SPECTRUM |
| Volume | 45 |
| Issue number | 2 |
| Early online date | 9 Jan 2023 |
| Publication status | Published - Jun 2023 |
Abstract
We investigate a specific truck scheduling problem at cross-docks in the postal service industry on an operational level aiming to maximise the number of duly parcels assuming fixed departure times of the outbound trucks. The inbound gates and the conveyors as means of transportation inside the hub constitute the bottleneck resources. As a novel extension, we propose flexible unloading speeds to efficiently utilise the scarce resources. We formalise the problem with a mixed integer program and explicitly incorporate controllable unloading speeds of the inbound trucks. We determine the computational complexity and develop a genetic algorithm to efficiently solve the problem. Our investigation focuses on both the performance of the genetic algorithm and the applicability of the results in a real-world environment by implementing scheduling policies in a simulation model that considers individual parcel interactions. Based on our experimental results, we can state that especially in problem settings with scarce conveyor capacities, our approach to incorporate controllable unloading speeds has the potential of significantly increasing the number of duly parcels.
Keywords
- Genetic algorithms, MIP, Parcel hubs, Scheduling policies, Simulation, Truck scheduling
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- Business, Management and Accounting (miscellaneous)
- Decision Sciences(all)
- Management Science and Operations Research
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In: OR SPECTRUM, Vol. 45, No. 2, 06.2023, p. 325-357.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - The parcel hub scheduling problem with limited conveyor capacity and controllable unloading speeds
AU - Bugow, Stefan
AU - Kellenbrink, Carolin
N1 - Funding Information: Open Access funding enabled and organized by Projekt DEAL.
PY - 2023/6
Y1 - 2023/6
N2 - We investigate a specific truck scheduling problem at cross-docks in the postal service industry on an operational level aiming to maximise the number of duly parcels assuming fixed departure times of the outbound trucks. The inbound gates and the conveyors as means of transportation inside the hub constitute the bottleneck resources. As a novel extension, we propose flexible unloading speeds to efficiently utilise the scarce resources. We formalise the problem with a mixed integer program and explicitly incorporate controllable unloading speeds of the inbound trucks. We determine the computational complexity and develop a genetic algorithm to efficiently solve the problem. Our investigation focuses on both the performance of the genetic algorithm and the applicability of the results in a real-world environment by implementing scheduling policies in a simulation model that considers individual parcel interactions. Based on our experimental results, we can state that especially in problem settings with scarce conveyor capacities, our approach to incorporate controllable unloading speeds has the potential of significantly increasing the number of duly parcels.
AB - We investigate a specific truck scheduling problem at cross-docks in the postal service industry on an operational level aiming to maximise the number of duly parcels assuming fixed departure times of the outbound trucks. The inbound gates and the conveyors as means of transportation inside the hub constitute the bottleneck resources. As a novel extension, we propose flexible unloading speeds to efficiently utilise the scarce resources. We formalise the problem with a mixed integer program and explicitly incorporate controllable unloading speeds of the inbound trucks. We determine the computational complexity and develop a genetic algorithm to efficiently solve the problem. Our investigation focuses on both the performance of the genetic algorithm and the applicability of the results in a real-world environment by implementing scheduling policies in a simulation model that considers individual parcel interactions. Based on our experimental results, we can state that especially in problem settings with scarce conveyor capacities, our approach to incorporate controllable unloading speeds has the potential of significantly increasing the number of duly parcels.
KW - Genetic algorithms
KW - MIP
KW - Parcel hubs
KW - Scheduling policies
KW - Simulation
KW - Truck scheduling
UR - http://www.scopus.com/inward/record.url?scp=85145818397&partnerID=8YFLogxK
U2 - 10.1007/s00291-022-00702-y
DO - 10.1007/s00291-022-00702-y
M3 - Article
AN - SCOPUS:85145818397
VL - 45
SP - 325
EP - 357
JO - OR SPECTRUM
JF - OR SPECTRUM
SN - 0171-6468
IS - 2
ER -