Cooperative Purchasing of LogisticsServices among Manufacturing Companiesbased on Semantic Web and Multi-Agent

System

Arkadiusz Kawa1, Pawel Pawlewski2, Paulina Golinska2 andMarcin Hajdul3

1Poznań University of Economics, al. Niepodległości 10, 61-875Poznań, Poland

arkadiusz.kawa@ue.poznan.pl2Poznan University of Technology, Strzelecka 11, 60-965

Poznań, Poland, paulina.golinska@put.poznan.pl,pawel.pawlewski@put.poznan.pl

3Institute of Logistics and Warehousing, Estkowskiego 6, 61-755 Poznań, Poland

marcin.hajdul@ilim.poznan.pl

Abstract. The common access to the broadband Internetallows small and medium enterprises (SME) simplerparticipation in various supply chains [3]. Howeverthe main problem still is lack of consistency betweenprocesses which are undertaken by various supplychain participants. The aim of this paper is topropose the concept of broader cooperation betweenmanufacturing companies based on semantic web andmulti-agent system. The background of this paperrefers to previous experiences of the authors byimplementation of the CORELOG project. It promotescooperation in logistics services among manufacturingcompanies located in the Bologna metropolitan area inorder to increase companies’ competitiveness as wellas environmental sustainability through therationalization of the logistics processes. Theapplication of semantic web and multi-agent system inthe above mentioned project allows the efficientautomatic data collection about logistics servicesproviders and their resources, as presented in theInternet.

Keywords: cooperative purchasing, logistics services,e-supply chain, semantic web, multi-agent system.

1 Introduction – project background

The project idea starts from the assumption that singlecompany’s intelligence does not necessary imply thesystem’s intelligence. In fact, through cooperationcompanies should rationalize their logistics processes,obtain cost savings and reduce empty shipments. At themoment many small and medium sized companies don’tactivate collaborations as they are traditionally managedlike “family enterprises”. This limits their ability toget potential opportunities offered by collaboration withother actors operating in the market. Thus, there is aneed to create commitment around companies’ collaborationthrough the promotion of public policies, conventions andother knowledge sharing moments.In described case, manufacturing companies decided to

start with a common purchasing approach that stands outfor less organizational costs and high savings due to thegrowing companies’ bargaining power and therationalization of logistics providers. Through the pilotimplementation the involved manufacturing and transportcompanies achieved significant cost savings. Theseexcellent results are actually the starting point for theinvolvement of further companies and the implementationof other collaborative solutions among SMEs in theEmilia-Romagna Region.The pilot implementations which were carried out with

the CORELOG project (financed under the Interreg IIIBCADSES EU Initiative), included I-LOG (IndustrialLogistics and intermodal transport for SMEs’ development)results with the objective to implement, in a regionalscale, the already developed medium and long termstrategy.

In collaboration with local associations, 5 companies,working in the mechanical district, were involved on avoluntary basis. The main activities realized were: review of companies’ strategies for the purchasing

of transport and logistics services; analysis of companies’ inbound and outbound flows

and related costs; verification of the scope of the coordinated

purchasing (inbound and/or outbound, or by trafficaxis) and estimation of the possible savings;

development of an action plan for the realizationof the proposed strategies and meetings withlogistics providers to discuss its feasibility;

definition of the medium and long term actions forevolving from common purchasing to integratedplanning.

As a result of the carried out activities companiesobtained savings from 53% to 61% of costs through thecommon purchasing of transport services in the Bologna-Milano route. The project was successful but there is still a big

area within it with improvement potential. There arestill many problems in the data collection phase. Infact, the companies involved in the pilot project haven’tgot the necessary information in their IT systems. Thisproblem is common to the majority of SME’s, as in manycases they don’t perform regular reporting and analysisof logistics flows. SME’s haven’t integrated informationsystems that allow monitoring of data related to theinbound freight flows. Moreover, as inbound flows arelinked to the company’s production system, it is moredifficult to implement collaborative solutions, as thiswould require significant changes in the planning andproduction process.Another problem regarding project’s results

implementation is the fact that the initial elaboratedsolution is dedicated to companies, which are located inthe proximity. There is no possibility to startcooperation with companies located in a bigger distance

due to the lack of automated searching, selection andsettling the initial cooperation conditions withpartners. In order to solve the above mentioned problems a new

model called MASEW (Multi-Agent based on Semantic Web) isproposed.

2 MASEW model

The MASEW model is a hybrid solution elaborated based onagent technology and semantic web concept including suchelements, as XML, Resource description Framework (RDF),and ontologies. Semantic web is an initiative that aimsto introduce standard description of the content inInternet in order to allow computer programs (eg. agents)processing of data and information appropriate to theirpurpose and meaning [1].The main feature of semantic web is its

interoperability. It is understood as an ability ofdifferent information systems to cooperate, safelyexchange data with predefined structure, as well as thefurther mutual usage of this data in order to createinformation. Communication between IT systems is possibleindependently of programming languages, platforms andoperations systems they use, and applied informationexchange standard. All the above mentioned features makethe concept of semantic web especially suitable forapplication in the e-supply chains.

Types of agents in MASEW model

In the distributed environment e.g. Internet two types ofmanaging/leader agents are common, namely stationaryagent (that has in command the other agents) and PSA(Polymorphic Self-Slimming Agent) with bimodal structure(an agent is composed of a sort of agent head, calledbootstrap agent, and agent body, called proxy agent) [4]. In

the MASEW model the first type of managing agent isimplemented. In order to gain information the LeaderAgent (LA) delegates collecting of predefined informationscope about potential business partners to group ofmobile agents. LA represents the particular interests ofcooperating companies and it is responsible forcooperation, communication, negotiation with the otheragents representing companies outside the cooperationnetwork. On the basis of collected information the LAmakes decisions regarding follow-up actions. Leader Agentis able to manage complex business processes. Itcooperates with groups of agents and creates multi-agentsystem, as followed:

Searching Agent (SA) – it is one the most mobileagents, which is responsible for searching inthe Internet suitable business partners andtrade partners according to the criteria definedin cooperation scenario. It is able to informthe Verifying Agent (see below) about semanticinconsistency of found information.

Offering Agent (OA) – represents companies (e.g.n-trier suppliers, logistics companies,distribution centers), which offer particularproducts and services

Informing Agent (IA) – it is responsible forsending information to LA about new attractiveoffers available (e.g. in e-market server orwww), as well as for informing agentsrepresenting trade partners about thepossibility of starting cooperation with LAafter fulfillment of defined criteria.

Negotiating Agent (NA) – represents tradepartners and on behalf of them it negotiatescooperation’s conditions with LA.

Verifying Agent (VA) – it verifies ontologiesand acts together with tool for semanticverification of information placed in the web bytrading partners.

Agents representing particular companies cooperatetogether and negotiate cooperation conditions in order to

reach common goal and at the same time to fulfill theoutlines of delegating institutions. It should bementioned that agents representing different, sometimescompeting companies can build up temporary alliances inorder to reduce the cost of logistics services (e.g.combined transportation). At the same time the logisticsservices providers could cooperate in order to fulfillthe requirements stated in the offer enquiry by client(e.g. when single company does not have enough capacity).The communication between agents and user is asynchronic,it means that the confirmation of message by receiver isnot required in order to continue the process execution.Agents and users are informed automatically about any newevent e.g. new offer arrival.The access to the semantic web does not require

application of any specialized IT systems. Informationcan be process in format that is readable andunderstandable for computer and any user. This solutiongives SMEs a better possibility to capture informationand exchange them within particular enterprises’ network,as well as it helps to build up business relations.Searching for potential business partners by agents in

semantic web, can be done superficial or in-depth. In thefirst case agents search only on these web sites withwords with strict defined meaning, not key words whichare often ambiguous. In the second case agent searchesmore precisely, analyses particular web sites content andpasses the results to other agents. The first solution isquicker but definitely less precise than the second one.

MASEW model implementation – example

In this example it is assumed that three companies (A, B,C) seek for carrier, which will organize freight fromBologna to Milano in Italy (see Fig.1.). These companieshave particular requirements regarding: mean oftransportation (truck with loading capacity of 24 t),delivery cycle 1 day and delayed payment period up to 60days. The pickup places are manufacturing sites at three

dispersed locations in Bologna, the places of deliveryare three distribution centers in Milano. The additionalrequirement is the participation of the carrier inexpress delivery forum. The organization of such process by hand would be time

consuming due to the fact that a company would have tovisit web pages of all potential carriers, as well as website of the express delivery providers’ forum in order toverify whether particular carrier is associated there. Inthe next step all potential carriers which don’t haveappropriate mean of transportation should be excluded.Additionally companies A, B, C would need to agree beforeall conditions are settled and approved all the changesbetween present and initial adjustments.

Fig.1. Companies’ cooperation by transport operations.

Application of the multi-agent system and semantic webfacilitates the above mentioned process. The procedurebelow presents the process of finding business partner byagents, following the defined scenario (see Fig. 2):

1. Companies (A, B, C) (or their IT systems) ordertheir searching agents (SA) execution of task(in this case it is defined as a choice ofcarrier for shipment of goods from Bologna toMilano according to optimization criteria).

2. SA through hyperlinks finds ontology definingkey words. Then it communicates with OArepresenting potential suppliers, carriers, etc.and collects their offers and passes them to LAfor analysis.

3. In case when SA has doubts about the content ofthe offer, it could command Verifying Agent (VA)to verify ontology and to contact its issuer.

4. Before offer choice LA questions supplier agentOA whether the offer is still valid. If not,then the whole procedure needs to be repeated.If the offer is still valid, then theappropriate resources are booked. LA can bookmultiple carriers, especially in case whenindividual carrier is not able to fulfilldemand. Particular OA (especially competitors)can create cooperation network (clustering).

5. After the offer is chosen LA informs agentsrepresenting business partners (NA) and startsnegotiations regarding number of routes,delivery dates, prices etc.

6. If the negotiations are successful, then thecooperation starts and agents sign thecommission of service purchase on behalf ofcompanies they represent.

7. When the cooperation is finished, LA stores thescenario in its database, such practice helpscompanies (A, B, C) to used successful scenarioin the future.

All parties involved in cooperation are informed aboutevery pre-transactional action and any identifieddisturbances in the process of order fulfillmentexecution (e.g. delays, lack of delivery, damages andreturns).

Fig. 2. Model of multi-agent system based on the semanticweb idea.

Resources description in MASEW model

The key factor in multi-agents systems is the homogeneouscommunication. It secures efficient common goalfulfillment and reduces misunderstandings. In order toexecute the above mentioned algorithm the communicationbetween agents representing different companies isneeded. In the MASEW model agents exchange messages basedon ACL (Agent Communications Language) using FIPAprotocol, especially from FIPA Communicative Act LibrarySpecification [2], which provides cooperation betweenagents systems. These protocols define syntactic,semantic, and pragmatic of created messages. Thissolution helps to send messages between independentlydesigned and developed agent systems. The structure ofACL with RDF message is presented below. It is an answerto query „Query Ref” number query00001, regarding thechoice of carrier for delivery of goods from Bologna toMilano in Italy.The message type „Inform” is defined in standard “FIPA

Communicative Act Library Specification” [2]. The messageis based on „logistics-services-providers” ontology,including the specification of logistics terms and their

meanings. The sender to this message is SA, which passesthe answer to LA’s query, with information about findingthe appropriate logistics services provider placed inBologna.

Example of the message „Inform” type in the FIPA protocolwith RDF.

(inform  :sender (agent-identifier :name SA)   :receiver (set (agent-identifier :name LA))  :content    "(result (action (find-resource : query...)) (“<?xml version=”1.0”?> <rdf:RDF> <res:Resource rdf:ID=”BestDeliveryLtd”> <loc:city>Bologne </loc:city> <loc:country>Italy </loc:country> <loc:streetAddress>14, Belle </loc:streetAddress> <loc:phone>+33 61 11 22 555 </loc:phone> </res:Resource> ...</rdf:RDF>”)  :language fipa-sl  :ontology logistics-services-providers  :in-reply-to query00001)

In MASEW model Resource Description Framework (RDF) andontologies are used at any stage of tasks execution offinding business partner by agents. It speeds up thesearching process because all data is well structured. Asa result easer data filtering and elimination ofunnecessary data is possible. Resource description ispresented below. This example includes the description of

found mean of transportation in XML format includingmeaning of this description in RDF. Schema vCard wasapplied for resource description. The resourceidentification number „LSP ID: H17N13M2T” is uniqueparameter, as well as the e-mail address “Roberto Luci”.

Example of the resource description in XML with theirmeaning in RDF.

<?xml version="1.0"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"xmlns:dc=http://purl.org/dc/elements/1.1/”

xmlns:vCard = "http://www.w3.org/2001/vcard-rdf/3.0#">   <rdf:Description rdf:about="LSP ID: H17N13M2T"> <dc:title>Truck 24 t</dc:title> <dc:creator rdf:resource=”mailto:luci@bestde.it”> <dc:subject>Transport, Bologne</dc:subject> <dc:description>Truck Box</dc:description> <dc:publisher>Best Delivery Ltd.</dc:publisher> <dc:contributor>Company A</dc:contributor> <dc:date>2009-11-15</dc:date> <dc:identifier>H17N13M2T</dc:identifier> <dc:language>Eng.</dc:language> <dc:coverage>Italy</dc:coverage> </rdf:Description>  <rdf:Description rdf:about=”mailto:luci@bestde.it”><vCard:FN>Roberto Luci</vCard:FN><vCard:Title>IT specialist</vCard:Title><vCard:Role>Programmer</vCard:ROLE><vCard:ORG> <vCard:Orgname>Best Delivery</vCard:Orgname> <vCard:Orgunit>IT Department</vCard:Orgunit> </vCard:ORG><vCard:TEL rdf:parseType="Resource"> <rdf:value>+33 61 11 22 555</rdf:value></vCard:TEL><vCard:ADR rdf:parseType="Resource"> <vCard:Street>14, Belle</vCard:Street> <vCard:Locality>Bologne</vCard:Locality>

<vCard:Pcode>00-111</vCard:Pcode> <vCard:Country>Italy</vCard:Country> </vCard:ADR> </rdf:Description></rdf:RDF>

3 Conclusions

Almost unlimited access to the Internet makes possiblecooperation in the area of logistics process not onlybetween big company but also SMEs. The lack ofconsistency of business process performed by particularentities and the variety IT systems used by companies,cause problems with automatic partners networking. Thepresented by authors MASEW model is solution that enablesefficient creation and automatic collection of data aboutcompanies and their resources published in the Internet.It broadens the possibilities of initial CORELOGproject’s results implementation. Agents representingparticular companies coordinate and establishcooperation’s conditions, in order to reach common goalof cost effectiveness.

References

1 Berners-Lee T., Hendler J., Lassila, O.: A New Form of WebContent that is Meaningful to Computers will Unleash aRevolution of New Possibilities, “Scientific American”, vol.284, no. 5. (2001).

2 FIPA Communicative Act Library Specification,http://www.fipa.org/specs/fipa00037

3 Fuks, K., Kawa, A., Wieczerzycki, W.: Dynamic Configurationand Management of e-Supply Chains Based on Internet PublicRegistries Visited by Clusters of Software Agents. In:HoloMAS 2007, LNAI, Springer-Verlag (2007).

4 Wieczerzycki W.: Polymorphic Agent Clusters – the Concept toDesign Multi-Agent Environments Supporting BusinessActivities, w: 2nd International Conference on Industrial

Applications of Holonic and Multi-Agent Systems – HoloMAS'05, Springer-Verlag, LNAI, Copenhagen, Denmark (2005).