Large-scale network partitioning for decentralized traffic management and other transportation applications

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 prerequisite for the DD solution process, a large domain must be partitioned into several smaller subdomains, with the key to success (of any DD partitioning algorithm) being the number of system boundary nodes. The lower this number, the more efficiently the subdomains can be processed. Although various transportation researchers have hinted at the use of DD, for example, in intelligent transportation systems-enabled decentralized traffic management, it is assumed that the partition is given. This article presents a simple, efficient, and effective algorithm to decompose a transportation network into a predefined number of interconnected subdomains such that the number of system boundary nodes is small (first priority) and the number of nodes in each subdomain is of similar size (second priority). To assess the effectiveness (in terms of minimizing the number of system boundary nodes) of the proposed Shortest Distance Decomposition Algorithm, it is compared with METIS version 5.1.0, currently among the most widely used graph partitioning algorithms worldwide. Using large-scale, real-world transportation test networks, it was found that the Shortest Distance Decomposition Algorithm is better than METIS in 21 of the 27 examples tested; on average, it provided (approximately) 42.0% of the system boundary nodes (as compared to METIS results) in our large-scale examples.