Abstract

The urban transit network design problem (UTNDP) is concerned with the development of a set of transit routes and corresponding schedules on an existing road network with known demand points and travel time. It is an NP-hard combinatorial optimization problem characterized by high computational intractability, leading to utilization of a wide variety of heuristics and metaheuristics in an attempt to find near-optimal solutions. This paper proposes a differential evolution approach to address the UTNDP by simultaneously determining the set of transit routes and their associated service frequency with the objective to minimize the passenger cost, as well as the unmet demand. In addition, a combined repair mechanism is employed to deal with the infeasible route sets generated from the route construction heuristic and the operators of the differential evolution. The proposed algorithm is evaluated on a well-known Mandl's Swiss network reported in the literature. Computational experiments show that the proposed algorithm is competitive according to the performance metrics with other approaches in the literature.

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