Dynamics in Logistics: Second International Conference, LDIC by Dieter Armbruster, M. P. M. Hendriks, Erjen Lefeber, Jan T. PDF

By Dieter Armbruster, M. P. M. Hendriks, Erjen Lefeber, Jan T. Udding (auth.), Hans-Jörg Kreowski, Bernd Scholz-Reiter, Klaus-Dieter Thoben (eds.)

ISBN-10: 3642119956

ISBN-13: 9783642119958

ISBN-10: 3642119964

ISBN-13: 9783642119965

The quantity includes the complaints of the second one overseas convention on Dynamics in Logistics LDIC 2009. The scope of the convention was once inquisitive about the identity, research, and outline of the dynamics of logistic strategies and networks. The spectrum reached from the making plans and modelling of approaches over leading edge equipment like self sufficient regulate and information administration to the hot applied sciences supplied by means of radio frequency identity, cellular verbal exchange, and networking. The becoming dynamics confronts the realm of logistics with thoroughly new demanding situations: It needs to develop into attainable to swiftly and flexibly adapt logistic approaches and networks to constantly altering stipulations. LDIC 2009 supplied a discussion board for the dialogue of advances in that topic. the amount contains one invited paper and of forty seven contributed papers divided into numerous topics together with mathematical modelling in shipping and creation logistics, routing in dynamic logistic networks, sustainable collaboration and provide chain regulate rules, details, communique, autonomy, adaption and cognition in logistics, radio frequency id in logistics and production networks, purposes in construction logistics, and logistic options for ports, box terminals, areas and services.

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Extra info for Dynamics in Logistics: Second International Conference, LDIC 2009, Bremen, Germany, August 2009, Proceedings

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Therefore, we choose the following approach: We use the ‘‘pull ahead’’ of the respective off-line solution in the current period, unless there is cumulated profit larger than zero. In this case only a certain fraction is used. That means: once there is a cumulated profit, it is not spend completely anymore. If there is no profit so far, we balance and try to keep the costs as low as possible: – We shift to the front if the off-line algorithm was unable to make any profit in the past; – We shift to the front if the off-line algorithm made a ‘‘large’’ profit in the past.

Here a symmetric matrix A is called strictly copositive, if xTAx C 0 for all x 2 Rn with xi C 0 and xTAx = 0 only if x = 0. Here x-: = min {0, x}. Theorem 3 A fluid network (a, l, P, C) is stable if there exists a K 9 K symmetric strictly copositive matrix A = (aik) such that, for k = 1,…,K, K X ai aik À min hik À i¼1 P i 2CðS k Þ J X j¼1;Sj6¼rðP k Þ  À min hik P i 2CðS j Þ \0; where H = M(I – P)A. 1 Adaption to Production Networks The fluid model introduced in Sect. 2 can be used to model and to analyse the dynamics of a production network.

W. Dangelmaier (&) and B. de B. -J. Kreowski et al. 1007/978-3-642-11996-5_4, Ó Springer-Verlag Berlin Heidelberg 2011 37 38 W. Dangelmaier and B. Degener The considered production system works taking into account the assumptions of the discrete lotsizing and scheduling problems (DLSP); the production of a product always covers complete time segments. IPF TP bit at bi kset i kqty it kstr i Bi0 Bsht iT xit BiT dset it dpdn it wi Set of products respectively product indices, i = {1,…,nPF} Time model with the set of time segments respectively their indices t = {1,…,nt} and the set of points of time for the end of a time segment (planning horizon)T = {0,…,nt}; t ¼ T Demand for product i in time segment t Available capacity in time segment t Production coefficient for product i Setup costs for product i Cost per unit for product i in time segment t Storage cost rate for product i per time segment t Initial inventory for product i Minimum inventory level for product i at the end of time segment t Lot size for product i in time segment t Demand for product i at the end of time segment t Setup costs for product t Production indicator for product i in time segment t Maximum amount of product i in time segment t The DLSP reduces the problem within a time segment to the decision whether to produce or not.

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Dynamics in Logistics: Second International Conference, LDIC 2009, Bremen, Germany, August 2009, Proceedings by Dieter Armbruster, M. P. M. Hendriks, Erjen Lefeber, Jan T. Udding (auth.), Hans-Jörg Kreowski, Bernd Scholz-Reiter, Klaus-Dieter Thoben (eds.)


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