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Deferment Control for Reoptimization : How to Find Fair Reoptimized Dispatches

Titelangaben

Rambau, Jörg:
Deferment Control for Reoptimization : How to Find Fair Reoptimized Dispatches.
In: Algorithms for Optimization with Incomplete Information. - Wadern : Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI) , 2005 . - (Dagstuhl Seminar Proceedings ; 05031 )

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Abstract

The german automobile association ADAC maintains a fleet of 1700 vehicles and has agreements with around 5000 service contractors. With these ressources, they help people whose cars have broken down on the road. Those people can call an ADAC help center, and within 10 seconds, an assignment of a service ressource to their request is made. At the same time, for all service vehicles, tours through the assigned requests have to be planned so as to minimize a certain (complicated) cost function for this so-called dispatch. No usefule knowledge about future requests is available at the time being. Therefore, the current policy of the automated system, developed in joint work with Sven O. Krumke, is to reoptimize the whole dispatch upon the occurrence of each relevant event, like the arrival of a new request. A similar online-optimization problem appears in the pallet elevator group control in a large distribution center of Herlitz PBS AG in Falkensee near Berlin. The problem with reoptimization policies in general is that, depending on the reoptimization objective, an arbitrarily large deferment of individual requests can be observed. In a way, individual requests are sacrificed in favor of a good performance according to the reoptimization objective. Nevertheless, w.r.t. the reoptimization objective, the reoptimization policies in the long run usually perform much better than the currently known policies that can not cause infinite deferment. Therefore, the goal is to modify reoptimization policies so as to prevent deferment. Sometimes deferment can be almost eliminated by enhancing the reoptimization objective with some terms that penalize waiting, but service in a fixed time can still not be guaranteed, and this kind of objective function engineering is a very time consuming tuning issue, interfering with the orgininal management objective. In this talk, the new policy of flow and makespan constrained reoptimization with reoptimization admission control is introduced. The main result is that, under d-reasonable load, for any reoptimization model, this policy yields a maximal flow time that is bounded by a constant 2d, depending only on the system load parameter d, not on the instance. In simulation experiments for the elevator group control problem we still obtain a very satisfactory average performance w.r.t. the reoptimization objective.

Weitere Angaben

Publikationsform: Aufsatz in einem Buch
Begutachteter Beitrag: Nein
Zusätzliche Informationen: Dagstuhl Seminar Proceedings laufen an der UB als elektron. Zeitschrift, ISSN 1862-4405
Institutionen der Universität: Fakultäten
Fakultäten > Fakultät für Mathematik, Physik und Informatik
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Mathematisches Institut
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Mathematisches Institut > Lehrstuhl Wirtschaftsmathematik > Lehrstuhl Wirtschaftsmathematik - Univ.-Prof. Dr. Jörg Rambau
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Mathematisches Institut > Lehrstuhl Wirtschaftsmathematik
Titel an der UBT entstanden: Ja
Themengebiete aus DDC: 500 Naturwissenschaften und Mathematik > 510 Mathematik
Eingestellt am: 05 Jun 2014 06:39
Letzte Änderung: 01 Dec 2014 12:40
URI: https://eref.uni-bayreuth.de/id/eprint/749