ABSTRACT
Train formation planning (TFP) is essential for rail freight logistics services. The fluctuation of railcar flows dramatically compared with before the outbreak of COVID-19. This paper studies train formation planning, considering three types of train services provided for railcar flow between pairs of technical stations (TS), including direct trains, district trains, and pickup trains. This paper introduces an optimization model with average railcars flow data (OMAD) and an optimization model with dynamic railcars flow data (OMDD) for the train formation planning based on TS under railcar demand fluctuation while minimizing railcar-hour consumption. The OMAD is a deterministic model, and the OMDD is a probability constraint model. To solve the OMDD, an approach for transforming probability constraints into deterministic constraints is presented. Various groups of scenarios are given to verify the effectiveness of the proposed models. [ FROM AUTHOR] Copyright of Journal of Industrial & Production Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)