THE VALUE OF INFORMATION SHARING IN A SERIAL

SUPPLY CHAIN WITH CENTRALISED AND DECENTRALISED

DECISION

Mansour Rached, Zied Bahroun, Belhassen Zouari

LIP2, FST, 2092, Manar 2 Tunis, Tunisia

Armand Baboli, Jean-Pierre Campagne

Université de Lyon, LIESP, INSA-Lyon, F-69621, Villeurbanne, France

Keywords: Information sharing, Supply chain, Downstream, Upstream information, Centralised, Decentralised

decision.

Abstract: 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.

1 INTRODUCTION

For many enterprises, the supply chain management

has become an important element of strategic

advantage to gain a competitive edge over their

competitors. In the sever competition times, the

enterprises want to obtain competition advantage,

they must carry on the cooperation with the other

echelons in the same supply chain, and try to

establish win-win cooperation relationship. The

information sharing is the foundation of the

cooperation between different links of supply chain,

and also is one main origin of the supply chain

advantages.

In this context, researches are numerous. The

existing works deal with the study of different types

of information sharing in different circumstances.

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). However, (Zhao and Qui, 2007) considered

simultaneously centralised and decentralised

decision. Concerning the provenance of the

information to share, on the one hand, many papers

have treated the case of downstream information

sharing (Agrawal et al., 2008), (Hsiao and Shieh,

2006), (Li and Zhang, 2008). 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. In (Li and

Zhang, 2008) authors present an objective function

which includes a cost formulation solved using

GAMS-CPLEX. In (Lehoux et al., 2007), authors

presented seven models aiming to study the value of

collaboration between a supplier and his customer.

269

Rached M., Bahroun Z., Zouari B., Baboli A. and Campagne J. (2010).

THE VALUE OF INFORMATION SHARING IN A SERIAL SUPPLY CHAIN WITH CENTRALISED AND DECENTRALISED DECISION.

In Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics, pages 269-272

DOI: 10.5220/0003004202690272

 SciTePress

To compare and analyse their developed models,

they use the solver CPLEX.

According to the above review, we propose to

study the effects of two information shared

simultaneously upon the supply chain performance

with several scenarios and circumstances. The

remainder of this paper is organised as follows.

Section 2 reviews the structure of studied supply

chain and introduces the different studied scenario.

Section 3 presents the simulation and analysis

results. Finally, conclusions are made in Section 4.

2 STRUCTURE OF STUDIED

SUPPLY CHAIN AND THE

RESOLUTION METHOD

The supply chain structure in this paper is a four-

echelon model Figure 1, which includes several

customers, one retailer, one warehouse and one

supplier. There are various items of information

which can be shared such as inventory level,

production capacity, etc. The shared information

refers to costumers’ demand coming from the

downstream of the supply chain and replenishment

leadtime coming from the upstream. We assume that

the costumers’ demand is normally distributed, the

leadtime between the supplier and the warehouse is

random and the leadtime between the warehouse and

the retailer is fixed for all periods.

Figure 1: Studied supply chain with information and

materiel flows.

We study the sharing of two information

simultaneously, which are the demand coming from

the downstream of supply chain and the leadtime

coming from the upstream.

To investigate the effect of information sharing

upon supply chain performance, for each studied

decision, four scenarios are designed with respect to

the two types of information mentioned above.

In the case of decentralised decision, the retailer

performs a local optimisation of its costs before

placing their orders. According to this order

quantity, the warehouse proceeds to a second local

cost optimisation to place an order to the supplier.

According to the centralised decision presented

in Figure 2, the four studied scenarios are as follows:

 Case of Replenishment Leadtime and Demand

Information Sharing: At the beginning of each

period, the decision maker (warehouse) is

informed about the exact replenishment

leadtime and the customers’ demand of the

current period. So, he calculates the order

quantity witch minimise the total system cost

according to the replenishment leadtime and

the exact demand of all periods.

 Case of Replenishment Leadtime Information

Sharing Only: The order quantity is calculated

by the decision maker according to the exact

replenishment leadtime and independently of

the customers’ demand.

 Case of Demand Information Sharing Only: In

this case, the warehouse calculates the order

quantity according to the exact customers’

demand and independently of replenishment

leadtime.

 Case of No Information Sharing: The decision

maker cannot choose the optimal order

quantity according to the replenishment

leadtime and/or the customers’ demand of

each period. So, he uses fixed values of both

information for all periods to calculate the

optimal order quantity.

3 EXPERIMENTAL RESULTS

In our simulation and in order to study the sensibility

and the robustness of our formulation, we use

different combinations of replenishment leadtime

and customers’ demand in each scenario as follows:

 Small leadtime

[

]

4 to1

, noted L1

;

 Large leadtime

[

]

21 to1

, noted L2

;

 High leadtime

[

]

12 to8

, noted L3

;

 First mean value of demand (high

demand)

380

, noted D1

;

 Small demand 100

, noted D2

;

Medium demand

230

, noted D3

We use in each simulation the same standard

deviation

=80.

ICINCO 2010 - 7th International Conference on Informatics in Control, Automation and Robotics

270

Figure 2: Activity diagram integrating all studied scenarios in a centralised decision.

In our work we deal with the problem of

optimisation based on a centralised (Table 1) and

decentralised decision (Table 2) using CPLEX.

 IS: Is the case of Information Sharing;

 NIS: Is the case of No Information Sharing;

 DemI: Demand Information;

 LtI: Leadtime Information.

Table 1: Total system cost in centralised decision.

DemI

TSC (10

)

IS NIS

LtI

IS 5,1347 8,4099

NIS 6,1216 11,1132

IS 3,9821 5,2154

NIS 4,7612 7,1256

IS 4,4782 6,8154

NIS 5,9373 10,0347

IS 5,1277 8,2367

NIS 7,4385 10,9521

IS 3,9482 5,9610

NIS 4,5659 6,9581

IS 6,0274 7,7147

NIS 6,8416 8,2618

IS 7,1639 9,2184

NIS 8,1374 10,3514

IS 4,1132 4,8952

NIS 4,5173 5,5901

IS 3,2467 5,1458

NIS 3,8962 7,7259

Table 2: Total system cost in decentralised decision.

DemI

TSC (10

)

IS NIS

LtI

IS 6,2704 10,5806

NIS 9,2921 12,8980

IS 5,2502 6,7198

NIS 6,4988 7,5044

IS 5,9443 7,8265

NIS 6,3447 10,5558

IS 6,9277 9,5627

NIS 8,8154 12,9171

IS 5,2502 7,2198

NIS 6,4059 8,2461

IS 6,2276 8,0747

NIS 6,7546 8,7996

IS 7,8686 9,8018

NIS 8,4053 11,0514

IS 5,3212 6,7635

NIS 5,8177 6,9859

IS 5,2606 7,5315

NIS 5,9153 9,9776

In Table 1 and Table 2, we present nine values of

simulations. Illustrated by the different combinations

of (L1

, L2

and L3

) and (D1

, D2

and D3

).For

each case we present TSC (10

) for four scenarios of

customers’ demand and replenishment leadtime

information sharing.

Based on the simulations in Table 1, we study

the centralised decision. Regarding the total system

cost, the results show an average percentage at

21.12% of reduction of logistic cost in the case of

THE VALUE OF INFORMATION SHARING IN A SERIAL SUPPLY CHAIN WITH CENTRALISED AND

DECENTRALISED DECISION

271

leadtime information sharing compared to the

scenario of no information sharing. Whereas the

demand information sharing compared to the

scenario of no information sharing presents an

average of 33.15% reduction of logistic cost.. When

the two information are simultaneously shared, we

obtain 44.66% of of logistic cost reduction

compared to the case of no information sharing. For

the decentralised decision illustrated by Table 2,

Compared to the case of no information sharing, we

can deduce 16.70% and 27.75% of reduction of

logistic cost concern, respectively, the case of

leadtime information sharing and, the case of

demand information sharing. When the two studied

information are simultaneously shared, we obtain

38.92% of reduction of logistic cost compared to the

case of no information sharing. In the case of no

information sharing, the centralised decision

presents 12.16% of reduction of logistic cost

compared to the case of decentralised decision.

Thus, the centralised decision compared to the case

of decentralised decision presents a percentage at

16.83%, 18.72% and 20.43% of reduction of logistic

cost concern, respectively, the case of leadtime

information sharing, the case of demand information

sharing and the case of two information shared

simultaneously. In the studied circumstances, we can

conclude that the information sharing and the

centralised decision present an advantage in terms of

reduction of logistic cost compared to the case of

decentralised decision.

4 CONCLUSIONS

In this paper, we are interested to the evaluating of

information sharing in supply chain. We treated in

particular the case of multi-product multi-echelon

supply chain. We studied the value of information,

specially two information shared simultaneously.

The firs information comes from the downstream

(demand) and the second come from the upstream

(leadtime) of supply chain. Moreover, the effect of

two kinds of decision has been also studied

(centralised and decentralised decision). We used the

traditional replenishment policies as a logistic

reference cost. The numerical experimentation

shows that the information sharing allows reducing

the total logistic costs (transportation and storage

costs). Moreover, the centralised decision is more

beneficial in terms of reduction of logistic cost

compared to the decentralised decision.

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