活动/讲座时间：2022-11-17 19:30
活动/讲座地点：线上腾讯会议：959-370-187
活动/讲座嘉宾：谢军
嘉宾介绍：
谢军，西南交通大学交通运输与物流学院教授，博士生导师，同济大学博士毕业，上海交通大学、美国西北大学博士后。主要从事大规模城市道路交通网络和公交网络的均衡建模，求解与优化研究。2018年获得美国国家科学委员会交通分会颁发的“The Stella Dafermos Best Paper Award”。主持有国家自然科学基金面上项目，国家自然科学基金青年项目，国家博士后国际交流项目派出计划，CFF-DIDI盖亚基金青年项目等。在国际期刊共发表论文SCI/SSCI论文十几篇，包括交通运输领域的主流期刊Transportation Science，Transportation Research Part A,B,C&E等。
主要内容：
This paper studies the continuous bi-criteria traffic assignment (C-BiTA) problem, which aims to find the distribution of agents with heterogeneous preferences in a network. The agents can be seen as playing a congestion game and their payoff is a linear combination of time and toll accumulated over the selected path. We discover a formulation that enables the development of a novel and highly efficient algorithm. The novelty of the algorithm lies in a decomposition scheme and a new potential function. Together, they reduce a complex assignment problem into a series of single boundary adjustment (SBA) operations, which simply shift flows between “adjacent” efficient paths connecting an origin-destination pair using a Newton method. The SBA algorithm is capable of producing highly detailed path-based solutions that hitherto are not widely available to C-BiTA. Our numerical experiments, which are performed on networks with up to forty thousand links and millions of origin-destination pairs, confirm the consistent and significant computational advantage of the SBA algorithm over the Frank-Wolfe (FW) algorithm, the widely-held benchmark for C-BiTA. In most cases, SBA offers a speedup of an order of magnitude. We also uncovered evidence suggesting the discrete approach-the standard multi-class formulation-is likely to produce far more used paths per origin-destination pair than C-BiTA, a potential computational disadvantage. Equipped with the proposed algorithm, C-BiTA, as well as its variants and extensions, could become a viable tool for researchers and practitioners seeking to apply multi-criteria assignment models on large networks.
