Integrated optimization of timetabling and berthing for dual-source trolleybus routes along corridors

Abstract

An integrated optimization approach for timetable and berth allocation has been proposed to address congestion issues at transportation nodes in common-route corridors for dual-source trolleybus systems. The study integrates travel times and the uncertainty of passenger demand to establish a bi-objective mixed-integer optimization model for minimizing the fleet sizes and required number of berths at common stations. By utilizing a Monte Carlo simulation to obtain the expected values of the fleet size and number of berths during actual route operations, the model can generate robust timetables and determine the number of berths at the common stations. The solving algorithm comprises a multi-objective particle swarm optimization with random weight variations. The results from a case study on four dual-source trolleybus routes in Beijing demonstrate that the model reduces the fleet size by 7.78% and number of berths at common stations by 11.11%. Consequently, this model can effectively reduce the long-term operational costs of bus companies and minimize the impacts of route operations on the road network.