Abstract
We present an efficient solver that produces clustered, balanced, and cost effective routes for distribution in a given geographical area. Through cloud computing, the optimization functionality is used by more than 30 Nordic newspaper distribution companies for solving Large-scale Node Edge Arc Routing Problems (NEARP) with route duration, route balancing, and route compactness constraints. First, we solve a capacitated clustering problem. The corresponding NEARP solution is further optimized through a combination of Iterated Local Search, Variable Neighborhood Search, and Large Neighborhood Search.
