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Online Network Optimization Problems
 In Developments from a
, 1998
"... . We survey results on online versions of the standard network optimization problems, including the minimum spanning tree problem, the minimum Steiner tree problem, the weighted and unweighted matching problems, and the traveling salesman problem. The goal in these problems is to maintain, with mini ..."
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. We survey results on online versions of the standard network optimization problems, including the minimum spanning tree problem, the minimum Steiner tree problem, the weighted and unweighted matching problems, and the traveling salesman problem. The goal in these problems is to maintain, with minimal changes, a low cost subgraph of some type in a dynamically changing network. 1 Introduction In the early 1920's Otakar Bor uvka was asked by the Electric Power Company of Western Moravia (EPCWM) to assist in EPCWM's electrification of southern Moravia by solving from a mathematical standpoint the question of how to construct the most economical electric power network [9]. In 1926 Bor uvka initiated the study of network optimization problems, by publishing an efficient algorithm for constructing a minimum spanning tree of a fixed network [9]. Certainly since the 1920's the underlying collection of sites that require electrification in southern Moravia has changed frequently as new sites ...
OnLine Algorithms: Competitive Analysis and Beyond
 In Algorithms and Theory of Computation Handbook
, 1999
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Order picking in an automatic warehouse: solving online asymmetric TSPs
 Mathematical Methods of Operations Research
, 1999
"... Abstract. We report on a joint project with industry that had the aim to sequence transportation requests within an automatic storage system in such a way that the overall travel time is minimized. The manufacturing environment is such that scheduling decisions have to be made before all jobs are ..."
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Abstract. We report on a joint project with industry that had the aim to sequence transportation requests within an automatic storage system in such a way that the overall travel time is minimized. The manufacturing environment is such that scheduling decisions have to be made before all jobs are known. We have modeled this task as an online Asymmetric Traveling Salesman Problem (ATSP). Several heuristics for the online ATSP are compared computationally within a simulation environment to judge which should be used in practice. Compared to the priority rule used so far, the optimization package reduced the unloaded travel time by about 40%. Because of these signi®cant savings our procedure was implemented as part of the control software for the stacker cranes of the storage systems. Key words: Traveling Salesman Problem, onlinealgorithm, automatic storage system 1
Incremental Algorithms: Solving Problems in a Changing World
, 2007
"... A typical algorithm for a combinatorial optimization problem is given a static set of input, and finds a single solution. This kind of algorithm cannot be used, however, in situations where the input and solutions change over time due to evolving constraints. This dissertation explores incremental p ..."
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A typical algorithm for a combinatorial optimization problem is given a static set of input, and finds a single solution. This kind of algorithm cannot be used, however, in situations where the input and solutions change over time due to evolving constraints. This dissertation explores incremental problems, one class of optimization problems that deals with this type of situation. An incremental algorithm is given a sequence of input, and finds a sequence of solutions that build incrementally while adapting to the changes in the input. Online algorithms also take in a sequence of input and produce incremental solutions; unlike their incremental counterparts, however, they do not know the input sequence in advance. We use our incremental results to better understand online algorithms and to indicate how their performance can be improved. Most combinatorial optimization problems can be extended to the incremental setting. We define general incremental formulations of covering and packing problems, and give incremental algorithms for such classes of problems. We study specific problems in detail, such as incremental bipartite matching, network flow,
Performance . . . PROCUREMENT MARKETS USING SEQUENTIAL AUCTIONS
, 2004
"... Competition in a transportation marketplace is studied under different supply/demand conditions, auction formats, and carriers’ behavioral assumptions. Carriers compete in a spot truckload procurement market (TLPM) using sequential auctions. Carrier participation in a TLPM requires the ongoing solu ..."
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Competition in a transportation marketplace is studied under different supply/demand conditions, auction formats, and carriers’ behavioral assumptions. Carriers compete in a spot truckload procurement market (TLPM) using sequential auctions. Carrier participation in a TLPM requires the ongoing solution of two distinct problems: profit maximization problem (chose best bid) and fleet management problem (best fleet assignment to serve acquired shipments). Sequential auctions are used to model an ongoing transportation market, where carrier competition is used to study carriers ’ dynamic vehicle routing technologies and decision making processes. Given the complexity of the bidding/fleet management problem, carriers can tackle it with different levels of sophistication. Carriers ’ decision making processes and rationality/bounded rationality assumptions are analyzed. A framework to study carrier behavior in TL sequential auctions is presented. Carriers ’ behavior is analyzed as a function of fleetmanagement technology, auction format, carrier bounded rationality, market settings, and decision making complexity. The effects of fleet management technology asymmetries on a competitive