TY - GEN
T1 - Online make-to-order joint replenishment model
T2 - 19th Annual ACM-SIAM Symposium on Discrete Algorithms
AU - Buchbinder, N.
AU - Kimbrel, T.
AU - Levi, R.
AU - Makarychev, K.
AU - Sviridenko, M.
PY - 2008
Y1 - 2008
N2 - In this paper, we study an online make-to-order variant of the classical joint replenishment problem (JRP) that has been studied extensively over the years and plays a fundamental role in broader planning issues, such as the management of supply chains. In contrast to the traditional approaches of the stochastic inventory theory, we study the problem using competitive analysis against a worst-case adversary. Our main result is a 3-competitive deterministic algorithm for the online version of the JRP. We also prove a lower bound of approximately 2.64 on the competitiveness of any deterministic online algorithm for the problem. Our algorithm is based on a novel primal-dual approach using a new linear programming relaxation of the offline JRP model. The primal-dual approach that we propose departs from previous primal-dual and online algorithms in rather significant ways. We believe that this approach can extend the range of problems to which online and primal-dual algorithms can be applied and analyzed.
AB - In this paper, we study an online make-to-order variant of the classical joint replenishment problem (JRP) that has been studied extensively over the years and plays a fundamental role in broader planning issues, such as the management of supply chains. In contrast to the traditional approaches of the stochastic inventory theory, we study the problem using competitive analysis against a worst-case adversary. Our main result is a 3-competitive deterministic algorithm for the online version of the JRP. We also prove a lower bound of approximately 2.64 on the competitiveness of any deterministic online algorithm for the problem. Our algorithm is based on a novel primal-dual approach using a new linear programming relaxation of the offline JRP model. The primal-dual approach that we propose departs from previous primal-dual and online algorithms in rather significant ways. We believe that this approach can extend the range of problems to which online and primal-dual algorithms can be applied and analyzed.
UR - http://www.scopus.com/inward/record.url?scp=55349091913&partnerID=8YFLogxK
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AN - SCOPUS:55349091913
SN - 9780898716474
T3 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
SP - 952
EP - 961
BT - Proceedings of the 19th Annual ACM-SIAM Symposium on Discrete Algorithms
Y2 - 20 January 2008 through 22 January 2008
ER -