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A primal-dual approximation algorithm for stochastic facility location problem with service installation costs. ... Ravi, R. and Sinha, A. (2004). Hedging uncertainty: approximation algorithms for stochastic optimization problems. ...doi:10.1111/itor.12183 fatcat:zztjtargz5fc5jm4wawim34hze
Algorithms 6(2), Article No. 37), for which only a logarithmic-factor approximation algorithm is known. ... I n this paper, we study approximation algorithms for two supply chain network design problems, namely, the warehouse-retailer network design problem (WRND) and the stochastic transportation-inventory ... The fifth author also thanks Gaidi Li, Xing Wang, and Chenchen Wu for helpful discussions. ...doi:10.1287/ijoc.1120.0522 fatcat:yxe6wh23tzehpmrwmt4mvggzri
To handle the computational difficulty in uncertain scenarios, we propose a Lagrange primal-dual learning algorithm to solve the model. ... We show that the algorithm allows the probability distribution of uncertainty to be unknown, and that desirable approximation can be achieved by utilizing historical data. ... The authors are grateful to the editors and anonymous reviewers for their valuable comments that improved the quality of this paper. ...doi:10.3390/en12122275 fatcat:oqmwmzwikvdivkec4bohn4ux6i
The authors develop an approximation algorithm for UFL based on a new version of the primal-dual algorithm. ... and k-median problems using the primal-dual schema and Lagrangian relaxation. ...
They cover approximately 30 years, from 1973 to 2003; they address: algorithms developed for the p-median problem and for a general formulation of uncapacitated location problems; the study of dynamic ... The objective of the present paper is to review my personal contributions in the field of uncapacitated facility location problems. ... A new iteration of the primal-dual algorithm takes place whenever better bounds are produced by either the primal or the dual. ...doi:10.1590/s0101-74382004000100003 fatcat:mmcc4zmverfehjmmyspwpni3fi
We also present approximation algorithms for facility location and some of its variants in the 2-stage recourse model, improving on previous approximation guarantees. ... We give a 2.2975-approximation algorithm in the standard polynomial-scenario model and an algorithm with an expected per-scenario 2.4957-approximation guarantee, which is applicable to the more general ... We also thank the anonymous reviewers who contributed greately to the clarity of the presented models and algorithms. ...arXiv:1712.06996v1 fatcat:acaaftgg45frnei3w6cfs2vkcu
In this article we consider a hybrid algorithm of Lagrangian Relaxation and artificial ants to solve an ILM problem previously proposed in the literature. ... Distribution network design (DND) attempts to integrate tactical issues such as inventory policies and/or vehicle routing decisions with strategic ones such as the problem of locating facilities and allocate ... Applying a relaxation over the primal problem leads to a sub-problem known as the dual problem which, when solved, usually provides lower bounds for the primal problem. ...doi:10.24846/v24i3y201502 fatcat:rwgxe4utzfaazfkewothvn3fwu
We propose a cost-sharing scheme for the k-level facility location game that is cross-monotonic, competitive, and 6-approximate cost recovery. ... This extends the recent result for the 1-level facility location game of Pál and Tardos. ... Moreover, we actually give a primal-dual algorithm for the k-FLP with a performance guarantee of 6. ...doi:10.1016/j.orl.2005.06.002 fatcat:gpoqxbsuibfclclhhpylwz3zzq
We resolve the status of this problem by giving a constant-factor primal-dual based approximation algorithm. ... While very general results have been developed for many problems in stochastic discrete optimization over the past years, the approximation status of the stochastic Steiner Forest problem has remained ... E.g., for problems like vertex cover, facility location, and set cover, where one can (approximately) solve the stochastic linear program to get fractional solutionseven if costs and demands are both random-and ...doi:10.1145/1536414.1536504 dblp:conf/stoc/GuptaK09 fatcat:jlxjrfrnvjebfeav2apsjloo5i
Lecture Notes in Computer Science
In this article we propose, for any > 0, a 2(1+ )-approximation algorithm for a facility location problem with stochastic demands. ... The incurred costs are the expected transportation costs from the demand points to the facilities, the operating costs of the facilities and the investment in inventory. ... We proposed a 2(1 + )-approximation algorithm for this model by giving both a (1 + , 1)-reduction to a soft capacitated facility location problem with general demands and a (2, 2)-approximating algorithm ...doi:10.1007/11496199_36 fatcat:g5kfelqhyzgvrbjk5k33arkkmq
This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. ... The first approach is to apply sample average approximation to approximate the two stochastic problem via sampling. ... , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ...doi:10.1007/s40092-017-0195-9 fatcat:pkfhxryf2na33fnliphtitvk4m
This work was supported by the National Science Foundation of China under general projects funding 61170232 and the 985 project funding of Sun Yat-Sen University. ... Jain and Vazirani  reduced the k-facility problem to the UFL in the following way: Suppose A is an approximation algorithm for the facility location problem. ... Consider a minimization problem and a primal-dual algorithm-an algorithm that is iteratively making primal and dual updates using linear programming relaxation of the problem and its dual. ...doi:10.1137/090781048 fatcat:6ncks3kiijdyjbsbiwjdjq5igm
We describe a Monte-Carlo simulation-based algorithm that integrates a sample average approximation scheme with a Benders decomposition algorithm to solve problems having stochastic independent transportation ... We study stochastic uncapacitated hub location problems in which uncertainty is associated to demands and transportation costs. ... Acknowledgments This work was partly funded by the Canadian Natural Sciences and Engineering Research Council under grants 227837-09 and 39682-10. This support is gratefully acknowledged. ...doi:10.1016/j.ejor.2011.02.018 fatcat:yxb3wiuymrbqdika37zmrqcczm
The method is illustrated through a facility location problem involving sellers and customers with conflicting preferences. ... Using modern decision rule approximations, we construct lower bounds on an optimistic version and upper bounds on a pessimistic version of the leader's problem. ... The authors thank Serkan Buldan for his help with the artwork. ...doi:10.1137/16m1098486 fatcat:ivlfzbm3dbd2detucubd5hr7ei
“Our primal-dual algorithm is motivated by the work of K. Jain and V. V. ... ., Los Alamitos, CA, 1999; see MR 2003c:68004] on facility loca- tion. Our rounding algorithm is motivated by the facility location algorithm of [D. B. Shmoys, E. Tardos and K. ...
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