Fundamentals of Large-Scale Crew Scheduling

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.

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Solving Large Scale Crew Scheduling Problems

Operations Research/Computer Science Interfaces Series - Interfaces in Computer Science and Operations Research ◽

10.1007/978-1-4615-4102-8_7 ◽

1997 ◽

pp. 183-194 ◽

Cited By ~ 3

Author(s):

Hai D. Chu ◽

Eric Gelman ◽

Ellis L. Johnson

Keyword(s):

Large Scale ◽

Crew Scheduling ◽

Scheduling Problems

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Uso da técnica de busca em vizinhança de grande porte para a programação da escala de motoristas de ônibus urbano

TRANSPORTES ◽

10.14295/transportes.v18i2.422 ◽

2010 ◽

Vol 18 (2) ◽

Author(s):

Gustavo Peixoto Silva ◽

Claudio Barbieri da Cunha

Keyword(s):

Local Search ◽

Large Scale ◽

Crew Scheduling ◽

Neighborhood Search ◽

Scheduling Problem ◽

Search Technique ◽

New Approach ◽

Proposed Model ◽

Belo Horizonte ◽

The City

Resumo: Este artigo apresenta uma nova abordagem para a resolução do Problema de Programação de Tripulações no Sistema de Transporte Público (PPT). O modelo se baseia na metaheurística GRASP cuja busca local é realizada pelo método da Busca em Vizinhança de Grande Porte, conhecida na literatura como Very Large-Scale Neighborhood Search. O grande diferencial da aplicação desta técnica de busca para o PPT é que, além de incorporar os movimentos de realocação e troca de tarefas, realizados tradicionalmente, ela também permite considerar trocas do tipo 3-optimal, 4-optimal, até o limite de n-optimal, para uma solução com n tripulações. A implementação da heurística proposta foi testada com dados de problemas reais de uma empresa que opera em Belo Horizonte, e os resultados foram comparados com as soluções adotadas pela empresa. Desta forma foi possível observar que o modelo apresentado neste trabalho produziu soluções mais econômicas do que aquelas praticadas pela empresa.Abstract: This paper presents a new approach to solve the Crew Scheduling Problem (CSP) for public mass transport system. The proposed model is based on the GRASP metaheuristic framework, where the local search is performed by the Very Large-Scale Neighborhood (VLSN) search technique. The great differential of this search technique applied to the CSP is that, in addition to task reassigning and swapping movements, adopted in previous work, it also allows considering 3-optimal, 4-optimal, up to n-optimal task movements, for a solution with n crews, yielding to improved solutions. The proposed heuristic was tested with data from real problems of a bus company operating in the city of Belo Horizonte, and the results compared to the manual solution adopted by the company. Thus it was observed that the model presented in this work have produced more economical solutions than those used by the company.

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