A Cooperative and Adaptive Variable Neighborhood Search for the Multi Depot Vehicle Routing Problem with Time Windows

In this paper we propose two cooperation schemes to compose new parallel variants of the Variable Neighborhood Search (VNS). On the one hand, a coarse-grained cooperation scheme is introduced which is well suited for being enhanced with a solution warehouse to store and manage the so far best found solutions and a self-adapting mechanism for the most important search parameters. This makes an a priori parameter tuning obsolete. On the other hand, a fine-grained scheme was designed to reproduce the successful properties of the sequential VNS. In combination with the use of parallel exploration threads all of the best solutions and 11 out of 20 new best solutions for the Multi Depot Vehicle Routing Problem with Time Windows were found.

Book review of “Germany in Transit: Nation and Migration, 1955-2005”. 588 pages, University of California Press, 2007, by Deniz Göktürk, David Gramling and Anton Kaes (eds.)

Though migration is an age-old feature of human activity, driven by various circumstances, its current place in the midst of global dynamics and the phenomenon of globalization is becoming increasingly critical. International immigration and its regulation have been largely shaped by the policies in the receiving countries, often determining preferences for nationality cohorts and work skills to satisfy their labor and human capital requirements. When immigration has been necessitated by political strife, host countries have displayed immense magnanimity as well. However, the growing realization of resource limitations and the strange quirks of cultural pluralism are in turn creating waves of dissonance. Literature and the media are now replete with an in depth look into the immigration debate in various nations of the world in trying to seek new directions and satisfactory solutions.

Exact Solutions to the Symmetric and Asymmetric Vehicle Routing Problem with Simultaneous Delivery and Pick-Up

In reverse logistics networks, products (e.g., bottles or containers) have to be transported from a depot to customer locations and, after use, from customer locations back to the depot. In order to operate economically beneficial, companies prefer a simultaneous delivery and pick-up service. The resulting Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP) is an operational problem, which has to be solved daily by many companies. We present two mixed-integer linear model formulations for the VRPSDP, namely a vehicle-flow and a commodity-flow model. In order to strengthen the models, domain-reducing preprocessing techniques, and effective cutting planes are outlined. Symmetric benchmark instances known from the literature as well as new asymmetric instances derived from real-world problems are solved to optimality using CPLEX 12.1.