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  • Institute for Operations Research and the Management Sciences (INFORMS)  (2)
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  • Institute for Operations Research and the Management Sciences (INFORMS)  (2)
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  • 1
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2017
    In:  INFORMS Journal on Computing Vol. 29, No. 2 ( 2017-05), p. 287-300
    In: INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 29, No. 2 ( 2017-05), p. 287-300
    Abstract: In this paper, we study a multisourcing supply network design problem, in which each retailer faces uncertain demand and can source products from more than one distribution center (DC). The decisions to be simultaneously optimized include DC locations and inventory levels, which set of DCs serves each retailer, and the amount of shipments from DCs to retailers. We propose a nonlinear mixed integer programming model with a joint chance constraint describing a certain service level. Two approaches—set-wise approximation and linear decision rule-based approximation—are constructed to robustly approximate the service level chance constraint with incomplete demand information. Both approaches yield sparse multisourcing distribution networks that effectively match uncertain demand using on-hand inventory, and hence successfully reach a high service level. We show through extensive numerical experiments that our approaches outperform other commonly adopted approximations of the chance constraint.
    Type of Medium: Online Resource
    ISSN: 1091-9856 , 1526-5528
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2017
    detail.hit.zdb_id: 2070411-2
    detail.hit.zdb_id: 2004082-9
    SSG: 3,2
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2013
    In:  INFORMS Journal on Computing Vol. 25, No. 3 ( 2013-08), p. 572-584
    In: INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 25, No. 3 ( 2013-08), p. 572-584
    Abstract: In 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 network design problem (STIND). These two problems generalize the classical uncapacitated facility location problem by incorporating, respectively, the warehouse-retailer echelon inventory cost and the warehouse cycle inventory together with the safety stock costs. The WRND and the STIND were initially studied, respectively, by Teo and Shu (Teo CP, Shu J (2004) Warehouse-retailer network design problem. Oper. Res. 52(3):396–408) and Shu et al. (Shu J, Teo CP, Shen ZJM (2005) Stochastic transportation-inventory network design problem. Oper. Res. 53(1):48–60), where they are formulated as set-covering problems, and column-generation algorithms were used to solve their linear programming relaxations. Both problems can be regarded as special cases of the so-called facility location with submodular facility costs proposed by Svitkina and Tardos (Svitkina Z, Tardos É (2010) Facility location with hierarchical facility costs. ACM Trans. Algorithms 6(2), Article No. 37), for which only a logarithmic-factor approximation algorithm is known. Our main contribution is to obtain efficient constant-factor approximation algorithms for the WRND and the STIND, which are capable of solving large-scale instances of these problems efficiently.
    Type of Medium: Online Resource
    ISSN: 1091-9856 , 1526-5528
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2013
    detail.hit.zdb_id: 2070411-2
    detail.hit.zdb_id: 2004082-9
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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