01517445

Component

For numerous large-scale engineering and science problems, domain decomposition (DD) has generally been accepted by research communities as among the most attractive methods to obtain solutions efficiently. As a pre-requisite for the DD solution process, a large domain must be partitioned into several smaller sub-domains, with the key to success (of any DD partitioning algorithm) being the number of system boundary nodes. The lower this number, the more efficient the sub-domains can be processed in parallel. Although various transportation researchers have hinted at the use of DD, for example, in decentralized traffic management, it is always assumed the partition is provided. This paper presents a simple, efficient and effective algorithm to decompose a transportation network into a predefined number of inter-connected sub-domains such that the number of system boundary nodes is small (first priority) and the number of nodes in each sub-domain is similar (second priority). This algorithm was based on a simplified version of the Polynomial (partitioned) Label Correcting Algorithm (P-LCA), rather than the classical (Bellman-Ford) LCA, coupled with simple heuristic rules. To assess the effectiveness (in terms of minimizing the number of system boundary nodes) of the proposed Shortest Distance Decomposition Algorithm (SDDA), it is compared with METIS, which is currently the most widely used graph partitioning algorithm world-wide. Using large-scale, real-world transportation test networks, it was found the SDDA is significantly better than METIS; the SDDA outperformed METIS in 23 of 27 examples, and on average provided (approximately) 46% fewer boundary nodes for large-scale examples.

This paper was sponsored by TRB committee ADB30(7) Paper Review Group #3. Alternate title: Efficient Shortest-Distance Decomposition Algorithm for Large-Scale Transportation Network Problems.

01503729

14-2921

English

18p

2014

Transportation Research Board 93rd Annual Meeting

Digital/other

Figures; References; Tables

Heuristic methods; Network nodes; Shortest path algorithms

Domain decomposition; Network decomposition; Transportation networks

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2014 Paper #14-2921

TRIS, TRB, ATRI

Jan 27 2014 3:00PM