起飞
运筹学
调度(生产过程)
国际机场
劳动力
TRIPS体系结构
布线(电子设计自动化)
作业车间调度
分解
计算机科学
列生成
车辆路径问题
工程类
数学优化
运输工程
运营管理
经济
数学
计算机网络
生态学
航空航天工程
生物
经济增长
作者
Giacomo Dall’Olio,Rainer Kolisch
出处
期刊:Transportation Science
[Institute for Operations Research and the Management Sciences]
日期:2023-06-02
卷期号:57 (5): 1231-1251
被引量:3
标识
DOI:10.1287/trsc.2022.0110
摘要
We address workforce optimization for ground handling operations at the airport, focusing on baggage loading and unloading. Teams of skilled workers have to be formed and routed across the apron to unload the baggage from the aircraft after a landing and to load it before takeoff. Such tasks must be performed within time windows and require a team of workers with different skill levels. The goal is to find a feasible plan that minimizes the sum of the tasks completion times. We formalize a variation of the workforce scheduling and routing problem, integrating team formation, hierarchical skills with downgrading, multiple trips, and different execution modes. We propose a solution approach based on branch-and-price-and-check and test it on real-world instances from a major European hub airport. We propose a model based on the Dantzig–Wolfe decomposition. In the pricing problem, we generate tours of teams as shortest paths with constrained resources in a network. In the master problem, we select an optimal set of tours that do not exceed the workforce availability. Our experiments show that the proposed algorithm can produce optimal solutions for small- and medium-sized instances and good or optimal solutions for large instances. The results also show that our approach outperforms the current airport dispatching policy. Funding: G. Dall’Olio was funded by the Deutsche Forschungsgemeinschaft [Grant Advanced Optimization in a Networked Economy Graduiertenkolleg 2201, Project 277991500]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0110 .
科研通智能强力驱动
Strongly Powered by AbleSci AI