By Theodore Tsekeris, Loukas Dimitriou, Antony Stathopoulos (auth.), Andreas Fink, Franz Rothlauf (eds.)
The booklet handy offers a cautious choice of appropriate purposes of CI tools for delivery, logistics, and provide chain administration difficulties. The chapters illustrate the present cutting-edge within the program of CI tools in those fields and may support and encourage researchers and practitioners to use and strengthen effective tools. a number of contributions during this e-book are prolonged models of papers awarded at EvoTransLog2007: the 1st ecu Workshop on Evolutionary Computation in Transportation and Logistics which used to be held in Valencia, Spain, in 2007. the vast majority of contributions are from extra, specifically chosen researchers, who've performed correct paintings in several parts of delivery, logistics, and provide chain administration. The aim is to widely hide consultant functions in those fields in addition to types of resolution techniques. at the software part, the contributions concentrate on layout of site visitors and transportation networks, automobile routing, and different very important facets of offer chain administration similar to stock administration, lot sizing, and lot scheduling. at the technique aspect, the contributions take care of evolutionary algorithms, neighborhood seek techniques, and scatter seek mixed with different CI options comparable to neural networks or fuzzy methods. The ebook is dependent based on the appliance domain names. therefore, it has 3 components facing site visitors and transportation networks, automobile routing, and provide chain management.
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Extra info for Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management
E. 400 monetary values, is set as the total available construction budget B, which can be regarded as suﬃcient to enhance the capacity of the existing network. In the C-NDP, the total available construction budget B for network construction plans equals 350 monetary units, which corresponds to the share of the amount needed to expand the capacity of all links to the upper bound. The convergence of the algorithm to the SUE conditions using the MSA heavily depends on the network conﬁguration and, particularly, the network size, the number of alternative paths connecting the O-D pair and the congestion level.
Estimation of time-dependent O-D demand and route choice from link ﬂows. In: Proceedings of the 81st Annual Meeting of the Transportation Research Board, National Research Council, Washington (2002) 15. : Adaptation in Natural and Artiﬁcial Systems, 2nd edn. MIT Press, Cambridge (1992) 16. : Origin-destination matrices estimated with a genetic algorithm from link traﬃc counts. Transportation Research Record 1771, 156–163 (2001) 17. : Real-time estimation of turning movement proportions from partial counts on urban networks.
Moreover, the variations of supply (capacity) can be considered as a common phenomenon in transport networks. There are several factors inﬂuencing capacity, including the composition of traﬃc, congestion eﬀects, road works, special events, and random phenomena like incidents and adverse weather conditions. Since the link and path travel times are closely related to link capacities, the travel time reliability depends on the ﬂuctuations of link capacities, which are usually referred to as link capacity degradation.
Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management by Theodore Tsekeris, Loukas Dimitriou, Antony Stathopoulos (auth.), Andreas Fink, Franz Rothlauf (eds.)