Optimizing Train-Stop Positions Along a Platform to Distribute the Passenger Load More Evenly Across Individual Cars

Crowding in metro trains is a major factor in determining both the passenger service level and the operator supply level. An uneven distribution in passenger load across individual cars of a train exacerbates the overall capacity loading of a metro transit system. A loading diversity factor has been adopted to adjust the effect when computing the capacity of a metro train. The passenger preference for a specific car of a train was found to depend upon minimizing the walking distance at destination stations. This paper is focused on the possibility that a passenger load could be more evenly dispersed by varying train-stop positions. This paper proposes a mathematical programming model to find the optimal train-stop position at each station of a hypothesized metro line. The objective function is set to minimize the discrepancies in passenger loading across individual cars. After applying a genetic algorithm to solve the proposed model, differentiating train-stop positions considerably improved the distribution of passenger loading.