A three-phase heuristic for the Fairness-Oriented Crew Rostering Problem

被引:4
作者
Breugem, Thomas [1 ]
Schlechte, Thomas [2 ]
Schulz, Christof [2 ]
Borndoerfer, Ralf [3 ,4 ]
机构
[1] Tilburg Univ, Sch Econ & Management, Warandelaan 2, NL-5037 AB Tilburg, Netherlands
[2] LBW Optimizat GmbH, Englerallee 19, D-14195 Berlin, Germany
[3] Zuse Inst Berlin, Takustr 7, D-14195 Berlin, Germany
[4] Free Univ Berlin, Dept Math & Comp Sci, Arnimallee 7, D-14195 Berlin, Germany
关键词
Crew planning; Fairness; Column generation; Variable-depth neighborhood search; COLUMN GENERATION APPROACH; INTEGRATED VEHICLE; DECOMPOSITION; METAHEURISTICS; EFFICIENCY; ALGORITHM; SEARCH;
D O I
10.1016/j.cor.2023.106186
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The Fairness-Oriented Crew Rostering Problem (FCRP) considers the joint optimization of attractiveness and fairness in cyclic crew rostering. Like many problems in scheduling and logistics, the combinatorial complexity of cyclic rostering causes exact methods to fail for large-scale practical instances. In case of the FCRP, this is accentuated by the additionally imposed fairness requirements. Hence, heuristic methods are necessary. We present a three-phase heuristic for the FCRP combining column generation techniques with variable-depth neighborhood search. The heuristic exploits different mathematical formulations to find feasible solutions and to search for improvements. We apply our methodology to practical instances from Netherlands Railways (NS), the main passenger railway operator in the Netherlands Our results show the three-phase heuristic finds good solutions for most instances and outperforms a state-of-the-art commercial solver.
引用
收藏
页数:12
相关论文
共 60 条
[1]   Reinventing crew scheduling at Netherlands railways [J].
Abbink, E ;
Fischetti, M ;
Kroon, L ;
Timmer, G ;
Vromans, M .
INTERFACES, 2005, 35 (05) :393-401
[2]  
Abbink E., 2014, THESIS ERIM
[3]  
Abbink E, 2018, INT SER OPER RES MAN, V268, P243, DOI 10.1007/978-3-319-72153-8_11
[4]   A survey of very large-scale neighborhood search techniques [J].
Ahuja, RK ;
Ergun, Ö ;
Orlin, JB ;
Punnen, AP .
DISCRETE APPLIED MATHEMATICS, 2002, 123 (1-3) :75-102
[5]   Fairness and Collaboration in Network Air Traffic Flow Management: An Optimization Approach [J].
Bertsimas, Dimitris ;
Gupta, Shubham .
TRANSPORTATION SCIENCE, 2016, 50 (01) :57-76
[6]   Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation [J].
Bertsimas, Dimitris ;
Farias, Vivek F. ;
Trichakis, Nikolaos .
OPERATIONS RESEARCH, 2013, 61 (01) :73-87
[7]   On the Efficiency-Fairness Trade-off [J].
Bertsimas, Dimitris ;
Farias, Vivek F. ;
Trichakis, Nikolaos .
MANAGEMENT SCIENCE, 2012, 58 (12) :2234-2250
[8]   Duty scheduling templates [J].
Borndoerfer, Ralf ;
Langenhan, Andreas ;
Loebel, Andreas ;
Schulz, Christof ;
Weider, Steffen .
PUBLIC TRANSPORT, 2013, 5 (1-2) :41-51
[9]   Integration of duty scheduling and rostering to increase driver satisfaction [J].
Borndörfer R. ;
Schulz C. ;
Seidl S. ;
Weider S. .
Public Transport, 2017, 9 (1-2) :177-191
[10]   Optimal duty rostering for toll enforcement inspectors [J].
Borndoerfer, Ralf ;
Sagnol, Guillaume ;
Schlechte, Thomas ;
Swarat, Elmar .
ANNALS OF OPERATIONS RESEARCH, 2017, 252 (02) :383-406