An optimization model for solving the route clustering problem
Taner Cokyasar, Amir Davatgari, Abolfazl Mohammadian · Procedia Computer Science · 2023
Clustering models and algorithms are important to tackle large-scale transportation and optimization problems. Studies considered various clustering strategies to condense the sizes of highly complex problems as part of heuristic solution approaches. In this study, we develop an optimization model to solve the route clustering problem (RCP). In the RCP, a given route, consisting of a series of nodes to be visited with a particular sequence, is to be partitioned into clusters such that cluster connection node distances are maximized, i.e., connector nodes are desired to be as apart from each other as possible. Meanwhile, the total distance taken in each cluster is also capped. A binary programming model is formulated to solve the RCP, and the source code is available at https://gitlab.com/tcokyasar/rcp. The program takes a set of nodes with a given visiting order, number of clusters desired, and a within-cluster distance threshold. It then returns labels for each node indicating which cluster it is assigned.