Mixed network design using hybrid scatter search

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.postprin

Bi-objective bimodal urban road network design using hybrid metaheuristics

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. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

A machine-to-loop assignment and layout design methodology for tandem AGV systems with single-load vehicles

10.1080/00207543.2010.489056International Journal of Production Research49123605-3633IJPR

Multi-objective discrete urban road network design

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A review of urban transportation network design problems

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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 with automobile and bus flow interaction. The problem considers the concurrent urban road and bus network design in which the authorities play a major role in designing bus network topology. The road network design deals with the decision making for new street constructions, lane additions to existing streets, lane allocations for two-way streets, and the orientations and locations of one-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 coverage of the bus network, the demand share of the bus mode, and the average travel generalized cost of bus passengers, are used to evaluate the network design scenarios. The problem is formulated as a multi-objective optimization model in which a modal-split/assignment model is included to depict the mode and route choice behaviors of travelers. The model is solved by the hybrid genetic algorithm and the hybrid clonal selection algorithm. The performance of these algorithms is presented and investigated by solving a number of test networks. © 2011 Springer Science+Business Media, LLC.postprin