TRAIN CIRCULATION PLANNING: QUANTITATIVE APPROACHES

Autor(es)

Vilela, Plinio ; Cachoni, Monica ; Vieira, Anderson ; Christofoletti, Luciano ; ASME

• Tipo de documento: Artigo Científico
• Fonte: PROCEEDINGS OF THE ASME JOINT RAIL CONFERENCE, 2017; v. N/A, p. 8-pg., 2017-01-01.

Resumo

(1) The railway traffic system is an important player in passenger and freight transportation. This paper aims to present a survey of optimization models for the most commonly studied rail transportation problems related to train scheduling. We propose a classification of models and describe their characteristics by focusing on model structure and algorithmic aspects. Most reviewed papers have been proposed during the last decades. Apart from a few exceptions, the survey concentrates on published and easily accessible material. We have also elected to limit ourselves to contributions dealing specifically with rail transportation planning in single and double tracks. Each model has different goals, such as, to minimize service delays, to reduce the unscheduled train stops or to minimize the total time a train has to remain motionless, specially to allow crossings. For each group of problems, we propose a classification of models and describe their important characteristics by focusing on model structure and algorithmic aspects. The literature review involve papers published since the 1970s, but recent publications suggest that the problem is still heavily investigated. The main approaches considered are those that focus on Mathematical Optimization and Simulation. The review also considers the approach used to generate the solution, the type of railroad (real or hypothetical), and the infrastructure characteristics used to represent the railroad model. Our analysis focuses on showing an overview of those planning models. (AU)

• Processo FAPESP: 15/50478-0 - Planejamento de circulação de trens com base em meta-planejamento
• Beneficiário: Plínio Roberto Souza Vilela
• Modalidade de apoio: Auxílio à Pesquisa - Pesquisa Inovativa em Pequenas Empresas - PIPE