This paper presents a parsimonious review on the definitions, classifications, objectives, constraints, network topology decision variables, and solution methods of the Urban Transportation Network Design Problem (UTNDP), which includes both the Road Network Design Problem (RNDP) and the Public Transit Network Design Problem (PTNDP). The current trend and gap in each class of the problem are discussed and future directions in terms of both modeling and solution approaches are given. This review intends to give a bigger picture of transportation network design problems, allow comparisons of formulation approaches and solution methods of different problems in various classes of UTNDP, and encourage crossfertilization between the RNDP and PTNDP research.

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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.

This paper addresses the problem of designing urban road networks in a multi-objective decision making framework. Given a base network with only two-way links, and the candidate lane addition and link construction projects, the problem is to find the optimal combination of one-way and two-way links, the optimal selection of network capacity expansion projects, and the optimal lane allocations on two-way links to optimize the reserve capacity of the network, and two new travel time related performance measures. The problem is considered in two variations; in the first scenario, two-way links may have different numbers of lanes in each direction and in the second scenario, two-way links must have equal number of lanes in each direction. The proposed variations are formulated as mixed-integer programming problems with equilibrium constraints. A hybrid genetic algorithm, an evolutionary simulated annealing, and a hybrid artificial bee colony algorithm are proposed to solve these two new problems. A new measure is also proposed to evaluate the effectiveness of the three algorithms. Computational results for both problems are presented.

In this paper a bimodal discrete urban road network design problem with bus and car modes is investigated. The problem consists of decision making for lane addition to the existing streets, new street constructions, converting some two-way streets to one-way streets, lane allocation for two-way streets, and the allocation of some street lanes for exclusive bus lanes. Two objectives are considered in the problem: maximization of consumer surplus, and maximization of the demand share of the bus mode. The interaction of automobile and bus flows are explicitly taken into account and a modal-split/assignment model is used to obtain the automobile and bus flows in the deterministic user equilibrium state. The main contribution of the paper lies in proposing a new network design problem that combines the road network design decisions with the decision making for bus networks. The problem is formulated as a mathematical program with equilibrium constraints. A hybrid of genetic algorithm and simulated annealing, a hybrid of particle swarm optimization and simulated annealing, and a hybrid of harmony search and simulated annealing are proposed to solve the problem. Computational results for a number of test networks are presented and investigated.Keywords Bimodal network design · Multi-objective · Elastic demand · Hybrid metaheuristics · Exclusive bus lanes

This paper aims to model and investigate the discrete urban road network design problem, using a multi-objective time-dependent decision-making approach. Given a base network made up with two-way links, candidate link expansion projects, and candidate link construction projects, the problem determines the optimal combination of one-way and two-way links, the optimal selection of capacity expansion projects, and the optimal lane allocations on two-way links over a dual time scale. The problem considers both the total travel time and the total CO emissions as the two objective function measures. The problem is modelled using a time-dependent approach that considers a planning horizon of multiple years and both morning and evening peaks. Under this approach, the model allows determining the sequence of link construction, the expansion projects over a predetermined planning horizon, the configuration of street orientations, and the lane allocations for morning and evening peaks in each year of the planning horizon. This model is formulated as a mixed-integer programming problem with mathematical equilibrium constraints. In this regard, two multi-objective metaheuristics, including a modified nondominated sorting genetic algorithm (NSGA-II) and a multi-objective B-cell algorithm, are proposed to solve the above-mentioned problem. Computational results for various test networks are also presented in this paper.

This research proposes a bi-level model for the mixed network design problem (MNDP). The upper level problem involves redesigning the current road links' directions, expanding their capacity, and determining signal settings at intersections to optimize the reserve capacity of the whole system.The lower level problem is the user equilibrium traffic assignment problem. By proving that the optimal arc flow solution of the bi-level problem must exist in the boundary of capacity constraints, an exact line search method called golden section search is embedded in a scatter search method for solving this complicated MNDP. The algorithm is then applied to some real cases and finally, some conclusions are drawn on the model's efficiency.

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