Collaboration Mechanism for Shared Returnable Transport Items in

Closed Loop Supply Chains

Fatima Ezzahra Achamrah

1,2

, Fouad Riane

1,2,3

, Abdelghani Bouras

1,2

and Evren Sahin

Complex Systems and Interactions, Ecole Centrale Casablanca, Casablanca, Morocco

Laboratoire Génie Industriel, Centrale Supelec, Paris Saclay University, France

Laboratory of Industrial Management and Innovation (LIMMII), University Hassan Premier, Morocco

Keywords: Collaboration Mechanisms, Closed Loop Supply Chain, Simulation, Returnable Transport Items.

Abstract: This paper addresses a relevant practical approach of collaboration in supply chains including reverse flows

of materials. The objective is to simulate a two-stage closed loop supply chains in which two producers use

reusable pallets to distribute their finished products to the same retailers. The producers supply raw materials

and new pallets they need from suppliers. For each producer, the flows of raw material, loaded/empty pallets

and finished products are triggered by information flows. Two simulation models are considered. In the first

model, supply chains are non-collaborative. Each producer manages his own pool of pallets. After receiving

replenishment orders, trucks deliver loaded pallets and simultaneously pick-up empty ones from retailers to

be returned to the producer. In the second model, the two producers share their pool of empty pallets. The

results show that collaboration can lead to economies of scale and costs reduction. They also highlight the

need for a third party to manage the entire system to promise mutual benefits for the concerned parties.

1 INTRODUCTION

A supply chain consists of a set of players including

raw material suppliers, manufacturers, wholesalers,

carriers, distributors and retailers. These entities are

involved in a series of processes and activities to get

a product or service to the customer. Supply Chain

Management (SCM) is generally recognized as the

biggest source of benefits for organizational

activities. It has also been the subject matter of many

papers in research literature in the fields of operations

management, operations research and economy since

supply chains are getting more complex.

Until now, to counteract complexity in supply

chains, the management emphasis has been on

exchanging information and coordinating the flow of

products between organizations. This is no more

enough to cope the increasing customer expectations,

the trend of online shopping and the pattern of

strongly individualized customer demand. The

growing complexity of most services and products

requires the use of more advanced (and costly)

resources. These resources can profit from large

economies of scale, which can be better caught if

resources are shared between organizations. The next

logical step is no longer focus only on coordinating

products and information flows, but also on sharing

assets in order to obtain maximum efficiency.

Increased concerns about the environmental

impact give rise to the emergence and the

development of the concept of closed-loop supply

chains (CLSC). A closed-loop supply chain consists

of both traditional forward activities and additional

return ﬂow processes. The return flow under study in

this paper concerns Reusable Transport Items (RTI).

RTI consist of all means used to assemble goods for

transportation, storage, handling and product

protection in a supply chain that returns goods for

further usage (Iassinovskaia, et al., 2016). Examples

include pallets as well as all forms of reusable crates,

trays, boxes, barrels, trolleys, pallet, etc.

As RTI are by their very nature reusable, they

flow in a closed loop within the supply chain: they

can be collected and returned empty to the sender, or

they can be reused by the receiver so that he can in

his turn ship his products. Therefore, there exist two

types of flows that must be managed simultaneously

(Talaei and al., 2016): forward flows, which

correspond to the traditional distribution of goods

loaded on RTI, and reverse flows, which correspond

to the picking up of empty RTI. Players act as

independent intermediaries to manage the processing

Achamrah, F., Riane, F., Bouras, A. and Sahin, E.

Collaboration Mechanism for Shared Returnable Transport Items in Closed Loop Supply Chains.

DOI: 10.5220/0009162402470254

In Proceedings of the 9th International Conference on Operations Research and Enterprise Systems (ICORES 2020), pages 247-254

ISBN: 978-989-758-396-4; ISSN: 2184-4372

247

of flows between manufacturers and distributors via

logistics service providers (LSPs). This management

requires tools for identifying assets, centralising

information flows, planning of production, delivery

and pick-ups, synchronisation of operations

according to the requirements of each actor, tracking

and traceability of products. This centralisation of

flows enables the pooling of services and resources

with a perspective of sharing between several actors.

The management of RTI is still far from being

controlled. The challenges are enormous given the

costs of managing froward and reverse flows, sorting,

handling and costs due to losses. The drive for cost

reduction coupled with the willingness (not to say the

constraint) to track assets makes auxiliary resources

such as RTI a crucial issue that can impact the

performance of the whole supply chain. Indeed, a

stock shortage of these RTI or a delay in the supply

or in the return leads to a delay in production or even

an interruption of product flows, with all the

consequences that this entails. In addition, their

mismanagement lengthens lead times and encourages

players to over-invest in these assets. Their difficult

identification increases idle inventory and

counterfeiting. In addition, their mishandling impairs

the quality of the products shipped. Finally, the key

players in the chain, in a growing concern to

participate in sustainable development, are concerned

about controlling natural resources and preserving the

environment, by promoting sharing RTI, which

considerably reduces the costs of storage, stock-outs,

and the production of packaging waste.

Consequently, companies are increasingly

wondering the possibility of joining their forces and

sharing their RTI assets to develop an unsurpassably

competitive advantage. Sharing RTI can boost the

competitiveness of the entire supply chain while

decreasing the cost of sourcing, inventory and

transportation. The consequent savings allow players

to achieve higher outcomes.

The main objective of this paper is to provide a

what-if analysis of a two-stage closed loop supply

chains where two non-competing manufacturers

deliver their products using compatible, similar and

smart RTI to a network of common retailers. A

simulation approach is used to quantitatively evaluate

the pros and cons resulting from collaboration and

RTI sharing.

The remainder of the paper is organized as

follows. The related literature is briefly reviewed in

section 2. The problem is described in section 3. In

section 4 the experimental design is provided, and the

results are presented in section 5. Section 6 concludes

the paper recalling the major’s takeaways and

research perspectives for further research in this area.

2 RELATED WORK AT GLANCE

Collaboration among companies is classified by using

certain characteristics.Direction (vertical/horizontal),

time horizon (short/middle/long term), functional

cooperation (joint functions vs. complementary

functions), degree of legal arrangements (from formal

contracts to informal agreements), and the number of

involved parties (Freitag et al. 2016).

Regarding direction there exist three types of

collaboration: Vertical, Horizontal and Lateral

collaboration. The term supply chain management

refers to vertical collaboration and integration among

parties in different levels of a supply chain. “The key

drivers of cost savings are inventory and transport

reduction, logistics facilities or equipment

rationalization, and sharing information” (Cruijssen,

2006). Vertical cooperation includes for example

Collaborative Planning, Forecasting and

Replenishment (CPFR), Vendor Managed Inventory

(VMI), etc. Horizontal collaboration takes place

between companies operating at the same level of the

supply chain. Some examples of application are

Manufacturer Consolidation Centers (MCCs), joint

route planning, and purchasing groups. Co-opetition

is a variant of horizontal cooperation. It takes place

when enterprises are simultaneously cooperating and

competing. It concerns no-core activities while

competition remains unchanged for core activities

(Bengtsson and Kock, 1999). Finally, lateral

cooperation is defined as a combination of vertical

and horizontal cooperation (Simatupang and

Shridharan, 2002). It aims at gaining more flexibility

by combining and sharing capabilities in both vertical

and horizontal directions.

According to (Freitag et al. 2016), physical assets

sharing turns out to be a new type of collaboration and

the most flexible one, while the contractual

complexity of the required legal regulations between

the companies is kept low. It can be a short, mid- to

long-term collaboration and be set up either

vertically, horizontally or laterally. Basically, every

ICORES 2020 - 9th International Conference on Operations Research and Enterprise Systems

248

Figure 1: Simulation modelling flowchart of a two-stage closed loop supply chain.

asset can be sharable, e.g., machine, warehouse,

transport means, returnable transport items (reusable

pallets, boxes; crates, etc.), production line, etc.

The most closely aligned work with this paper is

the research stream that addresses physical assets

sharing particulary RTI as a part of horizontal

collaboration. (Reaidy, et al. 2015) and (Makacia, et

al. 2017) study collaborative warehousing schemes.

(Yilmaz, Savasaneril, 2011), (Pan, et al. 2019) and

(Wang, et al. 2018) examine transportation resource

sharing between independent and non-competing

companies. (Mlinar, Chevalier, 2016), (Becker,

Sterna, 2016) and (Khajavi, Holmström, 2017)

investigate machinery and production capacity

pooling. As for RTI, all papers address the problem

as a part of VMI and/or develop decision supports

models for costs reduction within a stochastic or

deterministic environment. An example of

application can be found in: (Kim, et al. 2014), (Cobb,

2016), (Iassinovskaia, et al. 2016).

As far as we are concerned, this literature review

shows that few papers exist that evaluate the

performance of sharing physical assets between

different supply chains let alone in closed loop supply

chains and in managing the so-called returnable

transport items. Indeed, most of the paper address

problems where coordination is based either on

sharing of information or on joint decision-making.

This paper addresses a relevant practical approach of

horizontal collaboration in closed loop supply chains

including sharing returnable transport items.

3 PROBLEM DESCRIPTION

Simulation has been identified by numerous authors

as an effective tool to evaluate collaboration

mechanism design in supply chain (Pirard, et al

2011). This technique makes it possible to take into

account the complexity and the dynamic behavior of

a system and to consider the uncertainty related to its

environment (e.g. customer demand, lead time).

Simulation also enables the decision maker to

evaluate several control policies. Numerous

replications of the simulation model, corresponding

to many possible situations, can be carried out in

order to evaluate the robustness of the considered

design. Simulation does not guarantee an optimal

design. However, this technique offers the manager

real help in establishing and in evaluating the

consequences of his decisions. We devote the

reminder of the paper to explain the simulation model

we developed in order to highlight the benefits of

promoting RTI sharing. The advantages of economies

of scale can be viewed in terms of cost savings and

better operational performance. The supply chain

players can achieve a higher service level at lower

Collaboration Mechanism for Shared Returnable Transport Items in Closed Loop Supply Chains

249

costs if they agree on a suitable collaboration

mechanism.

In this paper we study a two-stage supply chain in

which two non-competing manufacturers deliver

their products to a network of common retailers using

compatible, similar and smart RTI, namely pallets.

The simulation model we be built captures the

supply chain physical entities at the different levels,

the material and information flows between entities

and the different decisions made at each level by each

manufacturer or retailer. The architecture of the

simulation model that corresponds to the two-stage

supply chain is depicted in figure 1. When a retailer

receives information on the demands of his

customers, he checks whether his stock of non-

palletized finished products is enough to meet them.

If not, he depalletizes the stock of loaded pallets. If

the stock reaches its replenishment point, or a new

demand has unmet finished product requirements, he

sends a replenishment order to a producer. When a

producer receives this order, he checks whether his

stock of finished and palletized products is enough to

satisfy the demand of his customer. If the quantities

requested exceed the available quantities, the

producer releases a production order. In the same

veins, at the level of each producer if the quantity of

raw material or the quantity of empty pallets is less

than a minimum inventory, a producer sends a

replenishment order to suppliers. Thereafter, the

trucks, loaded with the ordered pallets, leave the

depot and visit retailers to deliver loaded pallets and

simultaneously collect a quantity of empty pallets -as

long as the capacity of trucks is not exceeded.

We evaluate two scenarios. The first corresponds

to the non-sharing case. Each producer manages

separately his own pool of pallets. When a producer

(manufacturer) receives replenishment orders from

retailers, he puts trucks on way to deliver loaded

pallets and simultaneously pick-up his empty ones to

be returned. Empty pallets are stored separately at the

retailer location.

We consider a second case where the two

producers can share their pool of empty pallets. The

pallets are considered to be substitutable and there is

no need to keep them in sperate storages at costumer

locations. The quantity of empty pallets, collected by

each producer’s trucks, is whenever possible equal to

the quantity of full pallets delivered. In terms of

profits sharing, we suppose that each partner pays a

certain amount of dollars for each pallet used and

owned by the other producer. The damage of the

pallets is also supported. Each producer pays a

penalty cost per damaged pallet.

In a previous work (Iassinovskaia, et al. 2016), we

have studied a two-stage supply chain where non-

shared RTI are used to protect and distribute products

from a manufacturer to a set of customers. We

modelled the problem as a pickup and delivery

inventory-routing problem. We formulated a mixed-

integer linear program (MILP) taking into

consideration different constraints inherent in

transport, routing construction, truck and inventories

capacity and demand satisfaction. The objective

function to optimize is a combination of

transportation costs, inventory costs of empty and

loaded RTI at customers and at the depot,

maintenance costs and the cost to buy new RTI.

We have extended the scope of the problem to

include a set of manufacturers and developed a

mathematical model for solving an inventory routing

problem where RTI are shared between

manufacturers (Achamrah, et al. 2019). In the present

contribution, we would like to extend the scope of the

problem to focus on the global loss of efficiency that

supply chain players may experience. This can be

induced by the distributed nature of their decision

structure and their independent- not to say conflicting

objectives and way of operating that may hinder the

search a win-win agreement. Simulation makes it

possible to take into account the complexity and the

dynamic behavior of the system and to consider the

uncertainty related to its environment (e.g. customer

demand, lead time at each level).

4 EXPERIMENTAL DESIGN

We consider two manufacturers who manage

independently their pool of pallets and deliver to the

same set of 9 retailers. The simulation horizon

corresponds to 7 days. Trucks have a similar capacity

of 20 pallets to be loaded. Each pallet contains 8

boxes filled with finished products. The different

pallet storage locations have been designed with a

capacity of 1000 in terms of number of pallets. The

same goes for holding capacities of finished products

at the level of each producer and retailer.

A replenishment order for each retailer is an

inventory level less than or equal to 5 in terms of the

number of loaded pallets. As for manufacturers, the

replenishment order regarding empty pallets is an

inventory level less than or equal to 10. And the

replenishment order regarding raw material is an

inventory level less than or equal to 15. For both

producers, the order production point is an inventory

ICORES 2020 - 9th International Conference on Operations Research and Enterprise Systems

250

Table 1: Service level at the level of producer 1 and producer 2 for each scenario under consideration.

Table 2: Service level at the level of retailer 1, 2 and 3 for each scenario under consideration.

Retailer 1 Retailer 2 Retailer 3

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Non-

collaborative

supply

chains

1007

945

902

48.4

98.9

188

475

567

2035

75.1

81.1

286

206

526

942

64.8

82.1

Collaborative

supply

chains

318

912

1634

912

83.7

100.0

111

644

2430

85.3

96.8

199

613

1148

75.5

100

level less than or equal to 4 in terms of the number of

loaded pallets.

At the level of each retailer depalletization order

corresponds to an inventory level of finished products

less than or equal to 5. The demand the retailers have

to satisfy is assumed to be a random variable with a

normal distribution of mean of 13 and standard

deviation of 2 in terms of the number of finished

products of the producer 1 and a normal distribution

of mean of 20 and standard deviation of 2 in terms of

finished products of the producer 2. Palletization

order at the level of each producer corresponds to an

inventory level of loaded pallets less than or equal to

10. At the beginning of the simulation, the initial

inventory level of empty pallets at producer 1 is equal

to 30 and equal to 35 at level of producer 2. The initial

inventory level of finished products at producer 1 is

equal to 90 and equal to 60 at level of producer 2. The

initial inventory level of raw material is equal to 40 at

the producer 1 and to 30 at the producer 2. The initial

inventory levels of empty pallets and finished

products at the level of each retailer are equal to zero;

For both producers and retailer, the initial inventory

level of loaded pallets is equal to zero;

For both producer the cost to buy a new pallet is

$15/pallet. In terms of profits sharing, we suppose

that each producer pays $1.5 per period for each pallet

used and owned by the other producer. Each producer

pays $3 per unowned and damaged pallet. Lost sales

cost of $8 associated to each unsatisfied demand at

level of each producer.

5 ANALYSIS AND DISCUSSION

To assess each scenario, we selected the following

criteria: (1) Lost sales in terms of the number of filled

pallets at the level of each producer and in terms of

the

number of boxes at the level of each retailer ; (2)

Satisfied demands in terms of the number of filled

pallets at the level of each producer and in terms of

the number of boxes at the level of each retailer; (3)

Service level at each producer and retailer; (4) Cost to

buy new pallets; (5) the savings, loss and pay-out at

level of each producer.

All the simulation steps have been performed on

a personal laptop computer (Windows10, Intel Core

i5, 2.4GHz, 4GB of RAM) and with FlexSim 19.2.3.

Producer 1 Producer 2

# of new

purchased

pallets

Lost

sales

Satisfied

demands

Service

level (%)

# of new

purchased

pallets

Lost

sales

Satisfied

demands

Service

level (%)

Non-

collaborative

supply

chains

924 288 874 75.2 1123 284 906 76.1

Collaborative

supply

chains

690 105 1057 91.0 852 86 1104 92.8

Collaboration Mechanism for Shared Returnable Transport Items in Closed Loop Supply Chains

251

Table 3: Service level at the level of retailer 4, 5 and 6 for each scenario under consideration.

Retailer 4 Retailer 5 Retailer 6

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Non-

collaborative

supply

chains

331

139

571

245

63.3

63.8

289

170

134

78.7

31.7

325

364

522

52.8

85.6

Collaborative

supply

chains

804

347

89.1

90.4

124

197

299

91.2

70.7

268

421

537

61.1

88.0

Table 4: Service level at the level of retailer 7, 8 and 9 for each scenario under consideration.

Retailer 7 Retailer 8 Retailer 9

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Lost

sales

Product

Satisfied

demands

Product

Service

level

(%)

Product

Non-

collaborative

supply

chains

184

571

333

75.6

78.5

279

498

841

1960

75.1

79.7

255

258

2435

164

87.3

86.3

Collaborative

supply

chains

144

611

382

80.9

90.1

211

102

909

2356

81.2

95.9

175

2615

391

93.7

92.7

The number of replicate simulations is equal to

100. We analyse the effectiveness of the mechanism

under consideration assuming the following

assumptions:

 All the empty pallets present in the inventory at

the end of a period can be reused in the next

period;

 10% of pallets returned from retailers in each

period are considered damaged (unrepairable);

 Routing of trucks are not optimized and are

randomly constructed;

 Processing time required for palletization at the

level of each producer includes the time

necessary for sending replenishment orders to

suppliers and for receiving the ordered quantity

of new pallets and also the time to palletize

finished products.

As mentioned earlier, in this paper we consider two

producers who manage independently their pool of

pallets and deliver to the same set of retailers. After

receiving a replenishment order, they deliver loaded

pallets to a set of 9 retailers and collect

simultaneously empty pallets. The mechanism

thereafter by which the collaboration is established

between the two producers is examined.

Table 1, 2, 3 and 4 summarize the results of

simulation for all cases under consideration.

As we can notice and taking into account the 10%

of pallets damaged at each period, sharing pallets

allows both producers to reduce the number of pallets

bought from suppliers. Indeed, each producer can

replace the same quantities of new empty pallets he

needs to palletize by the substituted quantities of

empty pallets of the other producer. As a result, the

service level is enhanced. Furthermore, sharing

allows them to deliver more loaded pallets to retailers

(the number of the replenishment orders is increased)

and hence, enhance the service level at the level of

each retailer. It also enables to increase processing

time. Indeed, this processing rate includes, in addition

to the time required for palletization, the time

required for each producer to send replenishment

orders to suppliers and to receive the ordered quantity

of new pallets. Since each producer can use the other's

ICORES 2020 - 9th International Conference on Operations Research and Enterprise Systems

252

Table 5: Breakdown of costs at the level of producer 1 and 2 for each scenario under consideration.

Cost break down

($)

scenario:

non-collaborative supply

chains

scenario:

collaborative supply

chains (sharing pallets)

Producer 1 Producer 2 Producer 1 Producer 2

New pallets cost 13 860 16 845 10 350 12 780

Saving (regarding the purchased pallets) - - 3 510 4 065

Pay-out (include the costs resulting from

the use and/or the damage of unowned pallets)

- - 3 455 4 639.5

Lost sales 2 304 2 272 840 688

Saving (regarding buying new pallet and

the lost sales)

- - 4974 5649

Gain 334.5

2 194

pallets, he does not always have to buy the pallets

from the supplier each time his stock of empty pallets

reaches its replenishment point. Thus, processing

time is spent more on palletizing. This means that

palletizing and responding to retailers’ replenishment

orders can be done faster and more efficiently.

Table 5 gives more insights on the efficiency of

pallets sharing. The saving, loss and pay-out are

deducted according to the profit-sharing policy

adopted in this paper.

From the table 5 we notice that by minimizing the

number of pallets bought, sharing pallets allows both

producers to realise economies of scale and reduce

the cost of purchasing new pallets as compared to the

first scenario. As the one can see, producer 2 benefits

more from sharing as compared to the producer 1

(

$2 194 vs $334.5). Therefore, for a better coordination

and profit allocation, it would be convenient to call

upon a third-party service provider to manage the

whole system. Indeed, if a player would be in charge

of deliveries and pick-ups, inventory and transport

costs and the resulting carbon footprint would be

reduced. In this way, all parties including the

suppliers would benefit from the gains. Regarding the

share of information flows, if a player exists, he

would manage all the inventories and replenishments

orders. Then, he would synchronize the different

flows so that the inventory cost at all levels would be

reduced. Future studies can help to understand the

impact of the presence of a player on the performance

and behaviour of collaborative supply chains.

6 CONCLUSIONS

This paper addresses the issue of sharing physical

assets between independent producers in a two stages

supply chain. We design a simulation model to

investigate different ways players can manage their

reusable transport items within a closed loop supply

chain. The model compares two cases. The first case

considered two producers working autonomously and

delivering their finished products using pallets to the

same retailers. The second scenario considers sharing

the pool of empty pallets between producers as a

mechanism of collaboration. Material and

information flows, the inventory and transportation

costs at the level of each producer are analysed and

assessed in order to get insight on the effectiveness of

coordination. The result of simulation shows that the

coordination lead to economies of scale and cost

reduction. It also rises the need for a third party to

manage the whole system for promising mutual

benefits to the members.

Our future research plans include studying the

effect of resources sharing in a more complex supply

chains where uncertainties and risks are exposed, and

cooperative games are analysed using shapely value

for example which may allow to assess different

collaboration mechanisms starting from sharing

information to sharing trucks, warehouses and

machineries. On the other hand, managing the whole

supply chains and evaluating the performance of

supply chain requires a player. Various scenarios may

be explored with the help of simulation.

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