Abstract
Vehicle routing is a central task in a large number of private and public corporations (see, e.g., Golden, Raghavan, and Wasil [30]). Tours have to be planned in very diverse sectors of the economy, not only in the logistics and transport business but in virtually all industrial sectors producing physical goods. Variants of the vehicle routing problem manifest in a remarkably wide range of commercial and non-commercial enterprises: from waste/refuse collection to retail distribution; from construction material delivery planning to postal and express delivery routing; from inbound manufacturing component transportation to finished car distribution; from in-home primary health care service to hospital operations; from transportation network optimization to third Party Logistics (3PL) operation scheduling; and from bulk collection and delivery planning to passenger transportation routing. Hence, vehicle routing is key to logistics efficiency in industry, the public sector, and society in general. The high complexity of the vehicle routing problem renders purely human planning inadequate for most applications. Typically, human-made plans have a large potential for improvement. Also, non-assisted planning occupies valuable human resources. Therefore, high-quality software tools for decision support in vehicle routing are crucial to effective and efficient planning in many sectors of society.
