Plan-based bus bridging strategy during disruptions of urban rail networks.
Date:
• Constructed an Integer Linear Programming (ILP) model for “flexible scheduling” of buses to facilitate efficient passenger transportation during rail network disruptions. Developed a program using CPLEX to find the exact solution to the ILP model.
• Designed and implemented a heuristic algorithm in Python to expedite the solution process while consistently achieving optimal results. Introduced neighborhood actions in local search to enhance the algorithm’s performance, resulting in a solution that deviates by only 2.2% from the exact solution.