TY - GEN A1 - Heinz, Stefan A1 - Krumke, Sven A1 - Megow, Nicole A1 - Rambau, Jörg A1 - Tuchscherer, Andreas A1 - Vredeveld, Tjark T1 - The Online Target Date Assignment Problem N2 - Many online problems encountered in real-life involve a two-stage decision process: upon arrival of a new request, an irrevocable first-stage decision (the assignment of a specific resource to the request) must be made immediately, while in a second stage process, certain ``subinstances'' (that is, the instances of all requests assigned to a particular resource) can be solved to optimality (offline) later. We introduce the novel concept of an \emph{Online Target Date Assignment Problem} (\textsc{OnlineTDAP}) as a general framework for online problems with this nature. Requests for the \textsc{OnlineTDAP} become known at certain dates. An online algorithm has to assign a target date to each request, specifying on which date the request should be processed (e.\,g., an appointment with a customer for a washing machine repair). The cost at a target date is given by the \emph{downstream cost}, the optimal cost of processing all requests at that date w.\,r.\,t.\ some fixed downstream offline optimization problem (e.\,g., the cost of an optimal dispatch for service technicians). We provide general competitive algorithms for the \textsc{OnlineTDAP} independently of the particular downstream problem, when the overall objective is to minimize either the sum or the maximum of all downstream costs. As the first basic examples, we analyze the competitive ratios of our algorithms for the par ticular academic downstream problems of bin-packing, nonpreemptive scheduling on identical parallel machines, and routing a traveling salesman. T3 - ZIB-Report - 05-61 KW - Online Algorithms KW - Online Target Date Assignment Problem Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-8945 ER - TY - CHAP A1 - Hiller, Benjamin A1 - Krumke, Sven A1 - Rambau, Jörg ED - Liebling, T. ED - Duran, G. ED - Matamala, M. T1 - Reoptimization Gaps versus Model Errors in Online-Dispatching of Service Units for ADAC T2 - Latin-American Conference on Combinatorics, Graphs and Applications, Santiago de Chile 2004 Y1 - 2004 VL - 18 SP - 157 EP - 163 ER - TY - JOUR A1 - Hiller, Benjamin A1 - Krumke, Sven A1 - Rambau, Jörg T1 - Reoptimization Gaps versus Model Errors in Online-Dispatching of Service Units for ADAC JF - DISAM Y1 - 2006 VL - 154 IS - 13 SP - 1897 EP - 1907 ER - TY - GEN A1 - Ascheuer, Norbert A1 - Grötschel, Martin A1 - Krumke, Sven A1 - Rambau, Jörg T1 - Combinatorial Online Optimization N2 - In ``classical'' optimization, all data of a problem instance are considered given. The standard theory and the usual algorithmic techniques apply to such cases only. Online optimization is different. Many decisions have to be made before all data are available. In addition, decisions once made cannot be changed. How should one act ``best'' in such an environment? In this paper we survey online problems coming up in combinatorial optimization. We first outline theoretical concepts, such as competitiveness against various adversaries, to analyze online problems and algorithms. The focus, however, lies on real-world applications. We report, in particular, on theoretical investigations and our practical experience with problems arising in transportation and the automatic handling of material. T3 - ZIB-Report - SC-98-24 KW - Online Optimization KW - competitiveness KW - combinatorial optimization KW - real-world problems Y1 - 1998 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-3674 ER - TY - GEN A1 - Ascheuer, Norbert A1 - Krumke, Sven A1 - Rambau, Jörg T1 - The Online Transportation Problem: Competitive Scheduling of Elevators N2 - In this paper we consider the following online transportation problem (\textsc{Oltp}): Objects are to be transported between the vertices of a given graph. Transportation requests arrive online, specifying the objects to be transported and the corresponding source and target vertex. These requests are to be handled by a server which commences its work at a designated origin vertex and which picks up and drops objects at their starts and destinations. After the end of its service the server returns to its start. The goal of \textsc{Oltp} is to come up with a transportation schedule for the server which finishes as early as possible. We first show a lower bound of~$5/3$ for the competitive ratio of any deterministic algorithm. We then analyze two simple and natural strategies which we call \textsf{REPLAN} and \textsf{IGNORE}. \textsf{REPLAN} completely discards its schedule and recomputes a new one when a new request arrives. \textsf{IGNORE} always runs a (locally optimal) schedule for a set of known requests and ignores all new requests until this schedule is completed. We show that both strategies, \textsf{REPLAN} and \textsf{IGNORE}, are $5/2$-competitive. We also present a somewhat less natural strategy \textsf{SLEEP}, which in contrast to the other two strategies may leave the server idle from time to time although unserved requests are known. We also establish a competitive ratio of~$5/2$ for the algorithm \textsf{SLEEP}. Our results are extended to the case of ``open schedules'' where the server is not required to return to its start position at the end of its service. T3 - ZIB-Report - SC-98-34 KW - online optimization KW - competitive analysis KW - elevator Y1 - 1998 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-3779 ER - TY - CHAP A1 - Grötschel, Martin A1 - Krumke, Sven A1 - Rambau, Jörg A1 - Winter, Thomas A1 - Zimmermann, Uwe ED - Grötschel, Martin ED - Krumke, Sven ED - Rambau, Jörg T1 - Combinatorial Online Optimization in Real Time T2 - Online Optimization of Large Scale Systems Y1 - 2001 SP - 679 EP - 704 PB - Springer ER - TY - CHAP A1 - Grötschel, Martin A1 - Krumke, Sven A1 - Rambau, Jörg ED - Grötschel, Martin ED - Krumke, Sven ED - Rambau, Jörg T1 - Online Optimization of Complex Transportation Systems T2 - Online Optimization of Large Scale Systems Y1 - 2001 SP - 705 EP - 729 PB - Springer ER - TY - GEN A1 - Coja-Oghlan, Amin A1 - Krumke, Sven A1 - Nierhoff, Till T1 - Average Case Analysis of a Hard Dial-a-Ride Problem N2 - In the dial-a-ride-problem (DARP) objects have to be moved between given sources and destinations in a transportation network by means of a server. The goal is to find a shortest transportation for the server. We study the DARP when the underlying transportation network forms a caterpillar. This special case is strongly NP-hard in the worst case. We prove that in a probabilistic setting there exists a polynomial time algorithm which almost surely finds an optimal solution. Moreover, with high probability the optimality of the solution found can be certified efficiently. We also examine the complexity of the DARP in a semi-random setting and in the unweighted case. T3 - ZIB-Report - 03-12 KW - dial-a-ride-problem KW - average case analysis KW - MST-heuristic KW - Steiner trees KW - NP-hardness Y1 - 2003 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-7348 ER - TY - GEN A1 - Krumke, Sven A1 - Rambau, Jörg A1 - Torres, Luis Miguel T1 - Online-Dispatching of Automobile Service Units N2 - We present an online algorithm for a real-world vehicle dispatching problem at ADAC, the German Automobile Association. T3 - ZIB-Report - 02-44 KW - vehicle dispatching KW - soft time windows KW - online KW - real-time KW - ADAC Y1 - 2002 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-7117 ER - TY - GEN A1 - Hülsermann, Ralf A1 - Jäger, Monika A1 - Krumke, Sven A1 - Poensgen, Diana A1 - Rambau, Jörg A1 - Tuchscherer, Andreas T1 - Dynamic Routing Algorithms in Transparent Optical Networks An Experimental Study Based on Real Data N2 - Today's telecommunication networks are configured statically. Whenever a connection is established, the customer has permanent access to it. However, it is observed that usually the connection is not used continuously. At this point, dynamic provisioning could increase the utilization of network resources. WDM based Optical Transport Networks (OTNs) will shortly allow for fast dynamic network reconfiguration. This enables optical broadband leased line services on demand. Since service requests competing for network resources may lead to service blocking, it is vital to use appropriate strategies for routing and wavelength assignment in transparent optical networks. We simulate the service blocking probabilities of various dynamic algorithms for this problem using a well-founded traffic model for two realistic networks. One of the algorithms using shortest path routings performs best on all instances. Surprisingly, the tie-breaking rule between equally short paths in different wavelengths decides between success or failure. T3 - ZIB-Report - 02-35 KW - Dynamic Network Configuration KW - Routing and Wavelength Allocation KW - Transparent Optical Networks KW - Blocking Probability KW - Simulation Y1 - 2002 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-7025 ER -