A bilevel programming model for operative decisions on special trains: An Indian Railways perspective. Issue 3 (December 2018) - Kumar, Akhilesh; Gupta, Anjana; Mehra, Aparna
Abstract: This research develops decision support for railways on operational decisions of running special trains to tackle higher demand on specific routes during seasons of festivals and holidays. These operational decisions comprise of utilizing rolling-stocks and determining optimal fare-price structure in a competitive environment coerced by other travelling service providers. The influence on the demand-shares by the competitors of railways is incorporated in decision making to utilize the rolling-stock accordingly. A novel mixed integer bilevel programming model is proposed in which the railways is considered a leader and a group of all competitors to railways is a follower. The leader has to maximize the expected revenue by deciding on routes, rolling-stock assembly planning and fare-pricing for special trains subject to constraints on resources and the anticipated demand arising out of Nash-equilibrium fares of the follower. A diversified-elitist genetic algorithm is introduced to solve the proposed model. The proposed methodology is illustrated by taking a test situation from Indian Railways. The empirical analysis demonstrates the success of the proposed model in strategically addressing the fare-price competition and preparing the operational plan for running the special trains. Highlights: We study a problem of optimal operational decisions for railways to run special trains. The problem includes optimal fare-pricing decision for railways in a competitive environment. The fare-price reaction of competitors is captured in terms of Nash-equilibrium. A mixed integer bilinear bilevel programming model is proposed. A diversified-elitist genetic algorithm is applied to a test case of Indian Railways.