A single-product network design model with lead time and safety stock considerations

Sourirajan, Karthik; Özşen, Leyla; Uzsoy, Reha

doi:10.1080/07408170600941631

Cited by 78 publications

(50 citation statements)

References 33 publications

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“…There has been considerable effort devoted to extending the applicability of this model and to improving the associated solution procedures. Such extensions include the introduction of capacity constraints (Ozsen et al 2008), assuming a specific functional form for the lead time (Sourirajan et al 2007(Sourirajan et al , 2009, stochastic lead times (Tanonkou et al 2008), and relaxing the constraint that the variance-to-mean ratio of the random demands at each retailer are identical (Shu et al 2005;Tanonkou et al 2008;You and Grossman 2008).…”

Section: Literature Reviewmentioning

confidence: 99%

A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design

Diabat¹,

Richard

Codrington³

2011

Ann Oper Res

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Section: Literature Reviewmentioning

confidence: 99%

A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design

Diabat¹,

Richard

Codrington³

2011

Ann Oper Res

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“…Both UFLP and CFLP are classified as NP-hard problems. CFLP has the capacity constraints that limit the demand which can be served by each candidate location ( Sourirajan et al, 2007;Sourirajan et al, 2009). Geoffrion and Graves (1974) and Van Roy (1986) present models for the CFLP and propose Bender's decomposition approach and Lagrangian to solve the resulted problems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Supply network design is one of the strategic plans of supply management (Tang, 2006). The distribution networks' design is one of the most important decisions in supply chain (SC) where the primary objective is to determine the appropriate distribution centers (DCs) to supply retailers' demand (Sourirajan et al, 2007). The safety stock in cases where customer's demands are stochastic is influenced by lead time (Eppen & Martin, 1988;Karmarkar, 1993;Yang & Geunes, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…The safety stock in cases where customer's demands are stochastic is influenced by lead time (Eppen & Martin, 1988;Karmarkar, 1993;Yang & Geunes, 2007). Sourirajan et al (2007) consider a single product network design model that contains fixed facility location, the pipeline inventory and safety stock costs. The objective is to locate distribution centers at certain sites to serve groups of retailers.…”

Section: Introductionmentioning

confidence: 99%

“…This is a single product network design model lead time and safety stock consideration (SPNDLS) which consists of lead time and safety stock. SPNDSL is a non-linear integer programming problem which is recognized as NP-hard and Sourirajan et al (2007) propose heuristic method to find near-optimal solutions using Lagrangian heuristic. Sourirajan et al (2009) discuss the use of genetic algorithms (GA) for solving the SPNDLS problem.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A GRASP model in network design for two-stage supply chain

Javanshir¹,

Ghashti²

2011

msl

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We consider a capacitated facility location problem (CFLP) which contains a production facility and distribution centers (DCs) supplying retailers' demand. The primary purpose is to locate distribution centres in the network and the objective is the minimization of the sum of fixed facility location, pipeline inventory, safety stock and lost sales. We use Greedy randomized adaptive search procedures (GRASP) to solve the model. The preliminary results indicate that the proposed method of this paper could provide competitive results in reasonable amount time.

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Integrated multi‐echelon supply chain design with inventories under uncertainty: MINLP models, computational strategies

2009

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in Wiley InterScience (www.interscience.wiley.com).We address in this article a problem that is of significance to the chemical industry, namely, the optimal design of a multi-echelon supply chain and the associated inventory systems in the presence of uncertain customer demands. By using the guaranteed service approach to model the multi-echelon stochastic inventory system, we develop an optimization model to simultaneously determine the transportation, inventory, and network structure of a multi-echelon supply chain. The model is an MINLP with a nonconvex objective function including bilinear, trilinear, and square root terms. By exploiting the properties of the basic model, we reformulate this problem as a separable concave minimization program. A spatial decomposition algorithm based on the integration of Lagrangean relaxation and piecewise linear approximation is proposed to obtain near global optimal solutions with reasonable computational expense. Examples for specialty chemicals and industrial gas supply chains with up to 15 plants, 100 potential distribution centers, and 200 markets are presented. V

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A single-product network design model with lead time and safety stock considerations

Cited by 78 publications

References 33 publications

A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design

A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design

A GRASP model in network design for two-stage supply chain

Integrated multi‐echelon supply chain design with inventories under uncertainty: MINLP models, computational strategies

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