scholarly journals A Hybrid Approach for Solving Large Scale Crew Scheduling Problems

1999 ◽  
pp. 293-307 ◽  
Author(s):  
Tallys H. Yunes ◽  
Arnaldo V. Moura ◽  
Cid C. de Souza
Keyword(s):  
Large Scale ◽  
Hybrid Approach ◽  
Crew Scheduling ◽  
Scheduling Problems

Solving large scale crew scheduling problems

1997 ◽  
Vol 97 (2) ◽  
pp. 260-268 ◽  
Author(s):  
Hai D. Chu ◽  
Eric Gelman ◽  
Ellis L. Johnson
Keyword(s):  
Large Scale ◽  
Crew Scheduling ◽  
Scheduling Problems

Applying Constraint Programming and Integer Programming to Solve the Crew Scheduling Problem for Railroad Systems: Model Formulation and a Case Study

2021 ◽  
pp. 036119812110363
Author(s):  
Guei-Hao Chen ◽  
Jyh-Cherng Jong ◽  
Anthony Fu-Wha Han
Keyword(s):  
Integer Programming ◽  
Constraint Programming ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Hybrid Approach ◽  
Crew Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Systems Model ◽  
Crew Scheduling Problem

Crew scheduling is one of the crucial processes in railroad operation planning. Based on current regulations and working and break time requirements, as well as the operational rules, this process aims to find a duty arrangement with minimal cost that covers all trips. Most past studies considered this subject for railroad systems as an optimization problem and solved it with mathematical programming-based methods or heuristic algorithms, despite numerous logical constraints embedded in this problem. Few studies have applied constraint programming (CP) approaches to tackle the railroad crew scheduling problem. This paper proposes a hybrid approach to solve the problem with a CP model for duty generation, and an integer programming model for duty optimization. These models have been applied to the Kaohsiung depot of Taiwan Railways Administration, the largest railroad operator in Taiwan. The encouraging results show that the proposed approach is more efficient than the manual process and can achieve 30% savings of driver cost. Moreover, the approach is robust and provides flexibility to easily accommodate related operational concerns such as minimizing the number of overnight duties. Thus, this hybrid two-phase approach seems to have the potential for applications to the railroad crew scheduling problems outside Taiwan.

scholarly journals Solution of Multi-Crew Depots Railway Crew Scheduling Problems: The Chinese High-Speed Railway Case

2022 ◽  
Vol 14 (1) ◽  
pp. 491
Author(s):  
Chunxiao Zhao ◽  
Junhua Chen ◽  
Xingchen Zhang ◽  
Zanyang Cui
Keyword(s):  
Genetic Algorithm ◽  
Development Strategy ◽  
High Speed ◽  
Large Scale ◽  
Mathematical Formulation ◽  
Solution Space ◽  
Working Time ◽  
Crew Scheduling ◽  
Scheduling Problems ◽  
Improved Genetic Algorithm

This paper presents a novel mathematical formulation in crew scheduling, considering real challenges most railway companies face such as roundtrip policy for crew members joining from different crew depots and stricter working time standards under a sustainable development strategy. In China, the crew scheduling is manually compiled by railway companies respectively, and the plan quality varies from person to person. An improved genetic algorithm is proposed to solve this large-scale combinatorial optimization problem. It repairs the infeasible gene fragments to optimize the search scope of the solution space and enhance the efficiency of GA. To investigate the algorithm’s efficiency, a real case study was employed. Results show that the proposed model and algorithm lead to considerable improvement compared to the original planning: (i) Compared with the classical metaheuristic algorithms (GA, PSO, TS), the improved genetic algorithm can reduce the objective value by 4.47%; and (ii) the optimized crew scheduling plan reduces three crew units and increases the average utilization of crew unit working time by 6.20% compared with the original plan.

scholarly journals Solving large scale crew scheduling problems in practice

2011 ◽  
Vol 3 (2) ◽  
pp. 149-164 ◽  
Author(s):  
E. J. W. Abbink ◽  
L. Albino ◽  
T. Dollevoet ◽  
D. Huisman ◽  
J. Roussado ◽  
...  
Keyword(s):  
Large Scale ◽  
Crew Scheduling ◽  
Scheduling Problems

scholarly journals Clustering technique for large-scale home care crew scheduling problems

2017 ◽  
Vol 47 (2) ◽  
pp. 443-455 ◽  
Author(s):  
David Quintana ◽  
Alejandro Cervantes ◽  
Yago Saez ◽  
Pedro Isasi
Keyword(s):  
Home Care ◽  
Large Scale ◽  
Crew Scheduling ◽  
Scheduling Problems ◽  
Clustering Technique

scholarly journals Train Scheduling with Hybrid Answer Set Programming

2020 ◽  
pp. 1-31
Author(s):  
DIRK ABELS ◽  
JULIAN JORDI ◽  
MAX OSTROWSKI ◽  
TORSTEN SCHAUB ◽  
AMBRA TOLETTI ◽  
...  
Keyword(s):  
Real World ◽  
Large Scale ◽  
Hybrid Approach ◽  
Answer Set Programming ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Train Scheduling ◽  
Fine Grained ◽  
Difference Constraints ◽  
Answer Set

Abstract We present a solution to real-world train scheduling problems, involving routing, scheduling, and optimization, based on Answer Set Programming (ASP). To this end, we pursue a hybrid approach that extends ASP with difference constraints to account for a fine-grained timing. More precisely, we exemplarily show how the hybrid ASP system clingo[DL] can be used to tackle demanding planning and scheduling problems. In particular, we investigate how to boost performance by combining distinct ASP solving techniques, such as approximations and heuristics, with preprocessing and encoding techniques for tackling large-scale, real-world train-scheduling instances.

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