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

Javanshir, Hassan; Ghashti, Mahdis Haghighi

doi:10.5267/j.msl.2010.02.003

Cited by 3 publications

(1 citation statement)

References 38 publications

(43 reference statements)

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“…There are many applications of GRASP to solve engineering problems (Zapfel et al, 2010;Javanshir & Haghighi, 2011). There are some similarities between GRASP and Greedy construction method but there are some important changes between these two methods.…”

Section: Grasp Algorithmmentioning

confidence: 99%

Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

Ghobadian¹,

Tavakkoli–Moghaddam²,

Javanshir³

et al. 2012

IJIEC

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Cross docking play an important role in management of supply chains where items delivered to a warehouse by inbound trucks are directly sorted out, reorganized based on customer demands, routed and loaded into outbound trucks for delivery to customers without virtually keeping them at the warehouse. If any item is held in storage, it is usually for a short time, which is normally less than 24 hours. The proposed model of this paper considers a special case of cross docking where there is temporary storage and uses GRASP technique to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using GRASP method. The preliminary test results indicate that the GRASP method performs better than alternative solution strategies.

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Section: Grasp Algorithmmentioning

confidence: 99%

Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

Ghobadian¹,

Tavakkoli–Moghaddam²,

Javanshir³

et al. 2012

IJIEC

Self Cite

View full text Add to dashboard Cite

show abstract

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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Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using genetic algorithm

Ghobadian¹,

Tavakkoli–Moghaddam²,

Naderi-Beni³

et al. 2013

msl

Self Cite

View full text Add to dashboard Cite

Cross docking is one of the most important issues in management of supply chains. In cross docking, different items delivered to a warehouse by inbound trucks are directly arranged and reorganized based on customer demands, routed and loaded into outbound trucks for delivery purposes to customers without virtually keeping them at the warehouse. If any item is kept in storage, it is normally for a short amount of time, say less than 24 hours. In this paper, we consider a special case of cross docking where there is temporary storage and implements genetic algorithm to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using genetic algorithm. The performance of the proposed model is compared with alternative solution strategy, the GRASP method.

show abstract

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

Cited by 3 publications

References 38 publications

Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

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

Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using genetic algorithm

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