Tackling the rich vehicle routing problem with nature-inspired algorithms

Abstract In the last decades, classical Vehicle Routing Problem (VRP), i.e., assigning a set of orders to vehicles and planning their routes has been intensively researched. As only assignment order is already an NP-complete problem, application these algorithms in practice often fails take into account constraints restrictions that apply real-world applications, so called rich VRP (rVRP) are limited single aspects. this work, we incorporate main relevant requirements. We propose two-stage strategy Timeline algorithm for time windows pause times, Genetic Algorithm (GA) Ant Colony Optimization (ACO) individually problem find optimal solutions. Our evaluation eight different instances against four state-of-the-art shows our approach handles all given reasonable time.