Abstract

This study aims to investigate a robust network design problem to maximise the expected space-time accessibility, in which the origin-destination demand matrices are time-varying or unsynchronised under stochastic space-time scenarios. By defining the accessibility measure as the expected amount of accessible demand pairs, a linear 0–1 integer programming model is formulated to characterise the network design process. In order to find the near-optimal solutions for the problem of interest, an effective heuristic algorithm is proposed based on the framework of Lagrangian relaxation that decomposes the primal model into a series of tractable subproblems. Finally, the performance of the developed methods is demonstrated through numerical experiments in two networks with different scales. The results highlight the importance of considering robustness in transportation network design problems.

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