Abstract

We study a typical problem within the air cargo supply chain, concerning the transportation of standard Unit Load Devices (ULDs) from freight forwarders’ to ground handlers’ warehouses. First, ULDs are picked up by a set of available trucks at the freight forwarders’ premises within a time window. Next, they are delivered to the ground handlers, also within a time window, and discharged according to a Last In First Out (LIFO) policy. Due to space constraints, ground handlers have limited capacity to serve the trucks and waiting times may arise, especially in case freight forwarders do not coordinate their operations. Therefore, in this paper we consider a cooperative framework where this transportation is coordinated by a central planner. The goal of the planner is to find a proper routing and scheduling that minimizes the sum of the transportation and waiting times at the ground handlers’ warehouses, while satisfying the capacity of the trucks. We propose two mathematical formulations, one based on the routing and the other based on the packing aspect of the problem. To solve large instances of the problem, an Adaptive Large Neighborhood Search algorithm is also developed. With numerical experiments, we compare the performances of the two models and the metaheuristic, and we quantify the benefits of the proposed framework to reduce waiting times.

Highlights

  • Air cargo business represents a large share of airlines’ income, comparable to the one from first class passengers (Drljača, 2017)

  • We study a typical problem within the air cargo supply chain, concerning the transportation of standard Unit Load Devices (ULDs) from freight forwarders’ to ground handlers’ warehouses

  • We use the following notation: ID_FF_GH_ULD_PERC-TW_ND, where ID is the identifier of the instance within the same block, freight forwarder (FF) and ground handlers (GHs) are the number of FFs and GHs, respectively, ULD is the number of ULDs, PERC-TW is the time window percentage, and ND is the number of docks

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Summary

Introduction

Air cargo business represents a large share of airlines’ income, comparable to the one from first class passengers (Drljača, 2017). Larger FFs might already consolidate a considerable percentage of their shipments in-house into Unit Load Devices (ULDs), which are standardized containers for air cargo (Ankersmit et al, 2014). These ULDs. Received 4 June 2021; Received in revised form 20 November 2021; Accepted 1 January 2022. There is generally a strong supply/demand imbalance between the volume of trucks arriving to a GH warehouse and its actual processing capabilities.

Air cargo operations
Related pickup and delivery models
Problem formulation
Problem setting
GHDC-PDPTW: general notation
GHDC-PDPTW: a routing-based formulation
GHDC-PDPTW: a bin packing-based formulation
A metaheuristic approach
Initial solution generation
The ALNS algorithm
General description of instances
Metaheuristic parametrization and technical settings
Comparison between the non-cooperative and the cooperative framework
Analysis of ΔGH
Findings
Conclusions
Full Text
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