A method to evaluate downstream and upstream information sharing using the genetic algorithm

Rached, Mansour; Bahroun, Zied; Baboli, Armand; Campagne, Jean‐Pierre; Zouari, Belhassen

doi:10.1109/iccie.2009.5223809

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…The results show that decentralized SC system efficiency increases with price sensitivity, market scale, the supplier's cost while it decreases with production rate. The other papers focusing on centralized system are Fiala [30], Rached et al [56] and Ye et al [57].…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Information Sharing on Different Performance Indicators in a Multi-Level Supply Chain

2021

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Enterprises can use different methods/principles to obtain competitive advantages. Information sharing (IS) among supply chain (SC) partners is also one of these methods used in enterprises and it has positive effects on overall system performance like reduced inventory level, decreased cost, bullwhip effects and increased profit. In this paper, our aim is to present the impacts of IS on different costs like ordering, holding and penalty costs of each SC member and total system costs in multi SC. We want to show the effects of sharing different types of information simultaneously or separately on SC partners as cost change. Besides, this paper presents the situation of order quantity estimation according to the proximity of actual order quantity in decentralized or centralized demand sharing. A model is developed to determine IS influence on the cost of SC partners. Various IS scenarios are studied in this paper. The customer demand, warehouse order quantity and warehouse-manufacturer lead time are the shared information of scenarios. Results are tested and analysed by using analysis of variance (ANOVA).The findings of this study show that IS especially simultaneously sharing reduces system costs. Lead time sharing provides the lowest cost between other types of sharing. For every system member, holding cost reduces the most during IS. The more accurate demand forecasting is performed in centralized demand sharing compared to decentralized sharing.

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Section: Literature Reviewmentioning

confidence: 99%

The Impact of Information Sharing on Different Performance Indicators in a Multi-Level Supply Chain

2021

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“…Namely, the studied decision and the source of the share, etc. The centralised decision represents the most treated case (Chu and Lee, 2006), (Rached et al, 2009). The decentralised decision is treated in (Birendra et al, 2007), (Laux et al, 2004), (Li et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, (Chen and Yu, 2005), (Jia et al, 2007) and (Mehrabi et al, 2007) presented shared information which is coming from upstream. However, few papers considered the case of shared information coming simultaneously from the upstream and the downstream (Birendra et al, 2007), (Rached et al, 2009). The solver CPLEX is used in many recent works including a study of optimisation and the information sharing in supply chains.…”

Section: Introductionmentioning

confidence: 99%

The Value of Information Sharing in a Serial Supply Chain With Centralised and Decentralised Decision

Rached

Bahroun

Zouari

et al. 2010

Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics

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In this paper, we present a simulation based model in order to study the effects of information sharing in a serial supply chain. This chain is multi-product and multi-echelon. Our approach focuses on the study of two shared information simultaneously. The first one is the replenishment leadtime coming from the upstream and the second one is the customers' demand coming from the downstream of the supply chain. Thus, we present four scenarios of information sharing. The demand is supposed normally distributed and the leadtime is random. We develop a cost model consisting of holding, ordering, penalty and transportation costs. The difference of the optimal costs between each studied scenario represents the performance indicator of the information sharing. Two different decisions are considered in our work: centralised and decentralised. The developed model for each studied situation is solved by ILOG CPLEX integrated in a JAVA program. To conclude, the results of our numerical experimentations are analysed.

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A method to evaluate downstream and upstream information sharing using the genetic algorithm

Cited by 2 publications

References 16 publications

The Impact of Information Sharing on Different Performance Indicators in a Multi-Level Supply Chain

The Impact of Information Sharing on Different Performance Indicators in a Multi-Level Supply Chain

The Value of Information Sharing in a Serial Supply Chain With Centralised and Decentralised Decision

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