Hybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks

This paper addresses a bi-modal multi-objective discrete urban road network design problem. The problem includes the simultaneous design of urban road and bus networks in urban areas in which the authorities play a major role in designing bus network topology. The road network design consists of decision making for lane additions to the existing streets, new street constructions, determining the orientations and locations of one-way streets, and lane allocations for two-way streets. The bus network design is performed by keeping the terminal stations of the existing bus lines unchanged and redesigning the forth and back routes of each line. Four measures, namely user benefit, the demand share of the bus mode, the demand coverage of the bus network, and the average travel generalized cost of bus passengers, are used to evaluate the network design scenarios. The interaction of automobile and bus flows is explicitly modeled using a modal-split/assignment model to obtain the flows in the deterministic user equilibrium state. The problem is formulated as a mathematical program with equilibrium constraints. A hybrid of genetic algorithm and simulated annealing as well as a hybrid of clonal selection algorithm and simulated annealing are proposed to solve the problem. Computational results for a number of test instances are presented and investigated.