文献类型：期刊文献

英文题名：A Penalized Sequential Convex Programming Approach for Continuous Network Design Problems

作者：Guo, Lei[1];Yin, Haian[2];Zhang, Jin[2,3]

机构：[1]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Southern Univ Sci & Technol, Dept Math, Shenzhen 518055, Peoples R China;[3]Natl Ctr Appl Math Shenzhen, Shenzhen 518000, Peoples R China

年份：2025

外文期刊名：INFORMS JOURNAL ON COMPUTING

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001472327000001)】；

基金：Funding: This research was supported by the National Science Foundation of China [Grants 72131007, 72140006, 12271161, 12222106, and 12326605] , the Natural Science Foundation of Shanghai [Grant 22ZR1415900] , and Guangdong Basic and Applied Basic Research Foundation [Grant 2022B1515020082] .

语种：英文

外文关键词：continuous network design problem; bilevel program; difference of convex program; convex programming approach; decomposition

摘要：The continuous network design problem (CNDP) has been recognized as one of the most challenging issues in the field of transportation. Existing approaches to solving the CNDP are primarily heuristic without convergence guarantee or suitable for handling small networks because of the inherent nonconvexity arising from its bilevel hierarchical structure. An efficient and convergent approach for solving the CNDP on large networks has been fervently sought. In this paper, we present a novel convergent approach centered around exploiting the inherent convexity-related structure within the CNDP. We first demonstrate that the CNDP can be equivalently formulated as a difference of convex (DC) program with all involved functions being either convex functions or DC functions. Then, by exploiting the DC structure, we give a convex programming approximation for the CNDP and subsequently propose a penalized sequential convex programming approach. Finally, we show that the proposed method can yield an approximately stationary point under commonly used conditions. A numerical study is conducted on some real networks from a reputable network repository for transportation research. The numerical results demonstrate that the proposed method achieves better solutions with faster computational speed, particularly on larger networks, as compared with two heuristic approaches and two convergent approaches.