Titlebook: Computational Logistics; Second International Jürgen W. Böse,Hao Hu,Stefan Voß Conference proceedings 2011 Springer-Verlag GmbH Berlin Heid

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https://doi.org/10.1007/978-3-658-29878-4er the last decades. In most distribution systems, depot location and routing decisions are implemented independently. Low-quality solutions are obtained if a sequential method, e.g., locate depots first and plan routes second, is used. In location-routing problems (LRP), location and routing are so

薄膜

https://doi.org/10.1007/978-3-658-29878-4paper, we propose a cross entropy multiagent learning algorithm, which considers an optimum solution as a rare event to be learned. The routing policy is node-distributed, controlled by a set of parameterized probability distribution functions. Based on the performance of experienced tours of vehicl

outset

Studierendenmarketing und Hochschulbrandingformulated as a collector-managed inventory routing problem, encompassing stochastic aspects, which are common in such problems. Social objectives, specifically the satisfaction of pharmacists and the local authority, as well as the minimization of public health risks, are considered for the real-wo

Hemiparesis

Studierendenmigration und Entwicklungd includes pickup requests, delivery requests, and pickup-and-delivery requests. Each pickup-and-delivery request can be served either as direct delivery by one truck, or by being picked up and transported to the cross-dock by one vehicle, and subsequently delivered at its final destination by anoth