Online Algorithms for Multilevel Aggregation

• Published in: Operations research 2020-01, Vol.68 (1), p.214-232
• Main Authors: Bienkowski, Marcin, Böhm, Martin, Byrka, Jaroslaw, Chrobak, Marek, Dürr, Christoph, Folwarczný, Lukáš, Jeż, Łukasz, Sgall, Jiří, Thang, Nguyen Kim, Veselý, Pavel
• Format: Article
• Language: English
• Subjects: Agglomeration; algorithmic aspects of networks; Algorithms; Competition; Computer Science; Cost function; Equivalence; Hierarchies; lot sizing; Mathematical models; Multicasting; multistage assembly problem; Nodes; online algorithms; Online information services; Operations Research; Optimization; Replenishment; scheduling and resource allocation; Supply chains; TCP (protocol); Trees
• ISSN: 0030-364X; 1526-5463
• DOI: 10.1287/opre.2019.1847

Online Algorithms for Hierarchical Aggregation Problems Data and inventory aggregation problems arise in multicasting, sensor networks, communication in organization hierarchies, and in supply chain management. These problems are naturally online, in the sense that aggregation decisions need to be made without information about future requests. We study these problems with a general tree structure of links that can be used for deliveries. This generalizes some well-studied optimization problems: trees of depth one capture the TCP acknowledgment problem, and trees of depth two capture the joint replenishment problem. For trees of depth one and two, constant-competitive online algorithms are known. We solve a major open problem by giving a constant-competitive algorithm for trees of arbitrary (fixed) depth. The algorithm works for arbitrary waiting cost functions, including the variant with deadlines. In the multilevel aggregation problem (MLAP), requests arrive at the nodes of an edge-weighted tree T and have to be served eventually. A service is defined as a subtree X of T that contains the root of T . This subtree X serves all requests that are pending in the nodes of X , and the cost of this service is equal to the total weight of X . Each request also incurs waiting cost between its arrival and service times. The objective is to minimize the total waiting cost of all requests plus the total cost of all service subtrees. MLAP is a generalization of some well-studied optimization problems; for example, for trees of depth 1, MLAP is equivalent to the Transmission Control Protocol acknowledgment problem, whereas for trees of depth 2, it is equivalent to the joint replenishment problem. Aggregation problems for trees of arbitrary depth arise in multicasting, sensor networks, communication in organization hierarchies, and supply chain management. The instances of MLAP associated with these applications are naturally online, in the sense that aggregation decisions need to be made without information about future requests. Constant-competitive online algorithms are known for MLAP with one or two levels. However, it has been open whether there exist constant-competitive online algorithms for trees of depth more than 2. Addressing this open problem, we give the first constant-competitive online algorithm for trees of arbitrary (fixed) depth. The competitive ratio is O ( D 4 2 D ) , where D is the depth of T . The algorithm works for arbitrary waiting cost functio