Journal of Naval Scence and Engneerng 009 Vol. 5 No.3 pp. 38-54 A ETHOD FOR SELECTING THIRD PARTY LOGISTIC SERVICE PROVIDER USING FUZZY Erdal ÇAKIR Hakan TOZAN Ozalp VAYVAY Bahçeşehr Unversty Departent of Industral Engneerng IstanbulTürkye Turksh Naval Acadey Departent of Industral Engneerng IstanbulTürkye arara Unversty Departent of Industral Engneerng IstanbulTürkye erdal_cakır@yahoo.co htozan@dho.edu.tr ovayvay@eng.arara.edu.tr Abstract Logstcs servce provder selecton s a coplex ult crtera decson akng process; n whch decson akers have to deals wth the optzaton of conflctng objectves such as qualty cost and delvery te. Despte to the great varety of ethods and odels that have been desgned to help decson aker for ths process n lterature few efforts have been dedcated to develop systeatc approaches for logstcs servce provder selecton usng these predesgned ethods and odels. In ths study logstcs servce provder selecton decson support syste based on the fuzzy analytc herarchy process F) ethod s proposed ÜÇÜNCÜ PARTİ LOJİSTİK HİZET SAĞLAYICININ 3PL) BULANIK KULLANARAK SEÇİİ İÇİN BİR ETOT Özetçe Lojstk hzet sağlayıcının seç karar vercnn kalte alyet ve dağıtı zaanı gb brbr le çelşen brçok aacı eşzaanlı enyleesn gerektren karaşık çok ölçütlü br karar vere sürecdr. Lteratürde karar verclere bu süreçte yardıcı olak aacı le tasarlanan çok çeştl etot ve odeller olasına rağen tasarlanan bu etot ve odeller kullanarak lojstk servs 38
Erdal ÇAKIR Hakan TOZAN Özalp VAYVAY sağlayıcı seçne sstesel br yaklaşı getren çalışa çok az bulunaktadır. Bu çalışada bulanık ye dayalı br lojstk hzet sağlayıcı seç karar destek sste önerlştr Keywords: Logstcs Servce Provder Selecton Fuzzy 3PL Anahtar Keleler: Lojstk Servs Sağlayıcı Seç Bulanık 3PL. INTRODUCTION The logstcs servce provder selecton s a coplex ult-crtera proble that ncludes both quanttatve and qualtatve crtera soe of whch can conflct each other and s vtal n enhancng the copettveness of copanes [ ]. It s an portant functon of the logstcs departents as t brngs sgnfcant savngs for the organzaton. Whle choosng the approprate provder logstcs anagers ght be uncertan whether the selecton wll satsfy copletely the needs of the organzaton [3]. There are several suppler selecton applcatons avalable n the lterature. Vera and Pulan [4] exaned the dfference between anagers' ratngs of the perceved portance of dfferent suppler attrbutes and ther actual choce of supplers n an experental settng. They used two ethods: a Lkert scale set of questons and a dscrete choce analyss DCA) experent. Ghodsypour et al. [5] proposed an ntegraton of analytcal herarchy process ) and lnear prograng to consder both tangble and ntangble factors for choosng the best supplers and placng the optu order quanttes aong the such that the total value of purchasng becoes axu. has a wdespread applcaton area n decson-akng probles nvolvng ultple crtera n systes of any levels. The strength of the les n ts ablty of structurng coplex ult-person and ult-attrbute probles herarchcally and nvestgatng each level of the herarchy separately cobnng the results. In 00 Bevlacqua and Petron [] developed a syste for suppler selecton usng fuzzy logc FL). FL; whch was ntroduced by Zadeh n 965 wth hs poneer work Fuzzy Sets can sply be defned as a for 39
A ethod for Selectng Thrd Party Logstc Servce Provder Usng Fuzzy of atheatcal logc n whch truth can assue a contnuu of values between 0 and [6]. On the contrary to crsp dscrete) sets whch dvde the gven unverse of dscourse n to basc two groups as ebers and nonebers FL has the capablty of processng data usng partal set ebershp functons whch akes FL a strong devce for personatng the abguous and uncertan lngustc knowledge [7]. As fuzzy set theory becae an portant proble odelng and soluton technque due to ts ablty of odelng probles quanttatvely and qualtatvely those nvolve vagueness and precson [7] t has been successfully appled any dscplnes such as control systes decson akng pattern recognton syste odelng and etc. n felds of scentfc researches as well as ndustral and ltary applcatons. Kahraan et al. [8] used fuzzy F) to select the best suppler fr for a whte good anufacturer establshed n Turkey provdng the ost satsfacton. Duln and nnno [9] proposed a ult-crtera decson ad ethod proethee/gaa) to suppler selecton proble. They appled the odel to a d-szed Italan fr operatng n the feld of publc road and ral transportaton. Chan F. and Chan H. [0] reported a case study to llustrate an nnovatve odel whch adopts and qualty anageent syste prncples n the developent of the suppler selecton odel. Xa and Wu [] proposed an ntegrated approach of proved by rough sets theory and ult-objectve xed nteger prograng) to sultaneously deterne the nuber of supplers for eployng and the order quantty allocated to these supplers n the case of ultple sourcng ultple products wth ultple crtera and suppler s capacty constrants. In ths paper a decson support syste for logstcs servce provder selecton based on a F odel s desgned and pleented. The followng sectons of the paper are organzed as follow. In secton and Fuzzy odels are ntroduced. In secton 3 applcaton of fuzzy ethodology s deonstrated. Fnally research fndngs and dscussons are provded n secton n secton 4 and 5 respectvely. 40
Erdal ÇAKIR Hakan TOZAN Özalp VAYVAY. AND F ODEL. odel The analytc herarchy process ) was frst ntroduced by Saaty n 97 to solve the scarce resources allocaton and plannng needs for the ltary []. Snce ts ntroducton the has becoe one of the ost wdely used ultple-crtera decson-akng CD) ethods and has been used to solve any probles n dfferent areas of huan needs and nterests such as poltcal econoc socal and anageent scences. In the factors that affect the syste are desgned n herarchcally and the decson alternatves are evaluated wth par-wse coparsons of eleents n all levels. The scores of alternatves are calculated accordng to obtaned characterstcs. facltates decson akng by organzng perceptons feelngs judgents and eores nto a fraework that exhbts the forces that nfluence a decson. Once the herarchy has been constructed the decsonaker begns the prortzaton procedure to deterne the relatve portance of the eleents n each level. Prortzaton nvolves elctng judgents n response to questons about the donance of one eleent over another wth respect to a property. The scale used for coparsons n enables the decson-aker to ncorporate experence and knowledge ntutvely and ndcate how any tes an eleent donates another wth respect to the crteron [3]. The decson-aker can express hs or her preference between each par of eleents verbally as equally portant oderately ore portant strongly ore portant very strongly ore portant and extreely ore portant. These descrptve preferences would then be translated nto nuercal values 3579 respectvely wth 46 and 8 as nteredate values for coparsons between two successve qualtatve judgents. Recprocals of these values are used for the correspondng transposed judgents. Table shows the coparson scale used by. 4
A ethod for Selectng Thrd Party Logstc Servce Provder Usng Fuzzy Fnally all the coparsons are syntheszed to rank the alternatves. The output of s a prortzed rankng of the decson alternatves based on the overall preferences expressed by the decson aker. Senstvty analyss s used to nvestgate the pact of changng the prortes of the crtera on the fnal outcoe. The soluton procedure of the nvolve sx essental steps as follow [ 4 5 6 7 8 9]: Defne the unstructured proble and state clearly the objectves and outcoes. Decopose the coplex proble nto a herarchcal structure wth decson eleents crtera detaled crtera and alternatves). Eploy par-wse coparsons aong decson eleents and for coparson atrces. Use the egen value ethod to estate the relatve weghts of the decson eleents. Check the consstency of atrces to ensure that the judgents of decson akers are consstent. Aggregate the relatve weghts of decson eleents to obtan an overall ratng for the alternatves. Intensty of Iportance Defnton Equal Iportance 3 oderate Iportance 5 Strong Iportance 7 Very Strong Iportance Explanaton Two actvtes contrbute equally to the objectve Experence and judgent slghtly favor one actvty over another Experence and judgent strongly favor one actvty over another An actvty s favored very strongly over another; ts donance deonstrated n practce. 4
Erdal ÇAKIR Hakan TOZAN Özalp VAYVAY 9 Extree Iportance The evdence favorng one actvty over another s of the hghest possble order of affraton 4 6 8 For coprose between the above values Soetes one needs to nterpolate a coprose judgent nuercally because there s no good word to descrbe t.. F odel Table. The fundaental scale [4] There are any F ethods proposed by varous authors. These ethods are systeatc approaches to the alternatve selecton and justfcaton probles usng the concepts of fuzzy set theory and herarchcal structure analyss. The earlest work n F appeared n van Laarhoven and Pedrycz [0] whch copared fuzzy ratos descrbed by trangular ebershp functons. Buckley [] deternes fuzzy prortes of coparson ratos wth trapezodal ebershp functons. Sta et al. [] explore how artfcal ntellgence technques can be used to deterne or approxate the preference ratngs n. They conclude that the feed-forward neural network forulaton appears to be a powerful tool for analyzng dscrete alternatve ult-crtera decson probles wth precse or fuzzy ratoscale preference judgents. Later Nga and Chan [3] present a conventonal applcaton to select the ost approprate tool for supportng knowledge anageent KW) Wang and Chang [4] construct an analytc herarchy predcton odel based on the consstent fuzzy preference relatons to dentfy the essental success factors for an organzaton n KW pleentaton KW project forecast and dentfcaton of necessary actons before ntatng KW. Another pressve study s ade by Bozbura Beskese and Kahraan [5] n whch a F ethodology to prove the qualty of prortzaton of huan captal easureent ndcators under fuzzness s proposed. 43
A ethod for Selectng Thrd Party Logstc Servce Provder Usng Fuzzy In ths study the Chang s extent F s utlzed [6]. Let X x x x3... x n an object set and G g g g3... g n be a goal set. Accordng to the ethod of Chang s extent analyss each object s taken and extent analyss for each goal s perfored respectvely. Therefore extent analyss values for each object; g g... g... n can be obtaned where jg j =...) all are trangular fuzzy nubers TFN). [6]: The steps of Chang s extent analyss can be gven as n the followng Step : The value of fuzzy synthetc extent wth respect to the th object s defned as S j g j n j j g ) To obtan j g j perfor the fuzzy addton operaton of extent analyss values for a partcular atrx such that: j g l j j u j j j j j n j j j g ) and to obtan perfor the fuzzy addton operaton of jg j =...) values such that n j g j n n n l u 3) and then copute the nverse of the vector above such that: 44
Erdal ÇAKIR Hakan TOZAN Özalp VAYVAY 45 n n n n j j g l u 4) Step : As ) u l and ) u l are two trangular fuzzy nubers the degree of possblty of ) ) u l u l defned as: ) ) n sup y x V x y 5) and can be equvalently expressed as follows: ) ) d hgt V otherwse l u u l u l f f ) ) 0 The followng fgure llustrates equaton 6 where d s the ordnate of the hghest ntersecton pont D between and to copare and we need both values of V and V [4 ]. 6)
A ethod for Selectng Thrd Party Logstc Servce Provder Usng Fuzzy Fgure. The ntersecton between and [4 ]. Step 3: The degree possblty for a convex fuzzy nuber to be greater than k convex fuzzy = k) nubers can be defned by V... k ) V and ) n V ) 3... k and... and k Assue that da nv S S ) vector s gven by k 7) for k... n; k. Then the weght T d A ) d A )... d A n 8) W )) where... n) are n eleents. A Step 4: Va noralzaton the noralzed weght vectors are ) W d A ) d A )... d )) 9) where W s a non-fuzzy nuber. A n T 46
Erdal ÇAKIR Hakan TOZAN Özalp VAYVAY 3. THE APPLICATION OF F ETHODOLOGY The applcaton of the fuzzy approach s deonstrated for a edu-szed and growth-orented fast-ovng-consuer-goods FCG) copany whch s steadly ovng towards IT enableent of ts supply chan. It has partally outsourced ts outbound logstcs to carryng and forwardng agents. The copany s wllng to outsource ts entre logstcs actvtes. The goal s to choose the best logstcs servce provder for a case copany. So ths goal s placed at the top of the herarchy. The herarchy descends fro the ore general crtera n the second level to sub-crtera n the thrd level to the alternatves at the botto or fourth level. General crtera level nvolved fve ajor crtera: Cost of servce operatonal perforance fnancal perforance reputaton of the 3PL and long-ter relatonshps. Three logstcs servce provders are consdered for the decson alternatves and located the on the botto level of the herarchy. These are alternatve A B and C. Fgure llustrates a herarchcal representaton of selectng best logstcs servce provder decson-akng odel []. 47
A ethod for Selectng Thrd Party Logstc Servce Provder Usng Fuzzy Fgure. The decson herarch []. Provder A s asset-based and has ts own eans of transportaton dstrbuton and warehousng. B s slar to a 4PL copany wth advanced IT supply chan and change anageent capabltes. However the provder C s a non-asset-based copany and nstead of havng ts own physcal assets t reles on contractng the logstcs assets as per the requreent of the users. Qualfcatons of potental provders are llustrated n Table. For each of sub-crtera potental provders alternatve A B and C) have a level such as very low low noral hgh and very hgh. Ths classfcaton of alternatves accordng to ther capabltes helps akng par-wse coparson atrces. 48
Erdal ÇAKIR Hakan TOZAN Özalp VAYVAY an Crtera Cost of Servce Fnancal Perforance Operatonal Perforance Reputaton of the 3PL Long-ter Relatonshps Sub-Crtera Alternatve A Alternatve B Freght Prce Low Noral Hgh Alternatve C Ters of Payent Very Low Hgh Noral Extra Costs Hgh Noral Low Flexblty n bllng and payent Low Noral Hgh Fnancal stablty Noral Hgh Hgh Range of servces provded Low Hgh Very Hgh Qualty Noral Hgh Hgh IT capablty Noral Very Hgh Hgh Sze and qualty of fxed assets Hgh Noral Low Delvery perforance Low Hgh Noral Eployee satsfacton level Low Hgh Noral Flexblty n operatons and delvery Low Very Hgh Hgh arket share Noral Hgh Low Geographc spread and access to retalers Noral Hgh Noral arket knowledge Hgh Hgh Noral Experence n slar products Noral Noral Very Hgh Inforaton sharng Hgh Noral Hgh Wllngness to use logstcs anpower Noral Noral Hgh Rsk anageent Low Noral Hgh Qualty of anageent Low Noral Hgh Copatblty Low Hgh Hgh Cost of relatonshp Very Hgh Noral Hgh Table : Qualfcatons of potental provders After constructng the selecton odel herarchy par-wse coparsons ust be perfored systeatcally to nclude all the cobnatons of crtera/sub-crtera/secondary sub-crtera/alternatves 49
A ethod for Selectng Thrd Party Logstc Servce Provder Usng Fuzzy relatonshps. The crtera and sub-crtera are copared accordng to ther relatve portance wth respect to the parent eleent n the adjacent upper level. Geoetrc average s appled to cobne the fuzzy weghts of decson akers as; K K k W W k K k where W s the cobned fuzzy weght of decson eleent of K decson k akers W s the fuzzy weght of decson eleent of decson aker k and K llustrates the nuber of decson akers. The par-wse coparson atrx for the an attrbutes s bult and llustrated n the followng table and other atrces are constructed n the sae anner. 0) CST FP OP RPT LTR CST ) / 3/) ) 3/ ) / 3/) FP /3 ) ) /3 ) 3/ ) 3/ ) OP ) / 3/) ) 3/ 5/) 3/ 5/) RPT / /3 ) / /3 ) /5 / /3) ) / 3/) LTR /3 ) / /3 ) /5 / /3) /3 ) ) Table 3: Par wse coparson atrx for an attrbutes 4. RESEARCH FINDINGS The coparson of total weght of alternatves s showed that alternatve B whch has the hghest prorty weght s selected as a best logstcs servce provder. The logstcs servce provder B can fulfll the requred deands of the FCG case copany. The sequence of alternatves 50
Erdal ÇAKIR Hakan TOZAN Özalp VAYVAY accordng to ther portance weght s as follows: Alternatve B Alternatve C and Alternatve A. The prorty weghts collected fro each of par-wse coparson atrces of an crtera and alternatves are suarzed n the Table 4. The results calculated shows that the an crtera operatonal perforance s the ost portant factor for logstcs servce provder selecton. an Crtera an Crtera Pont Sub-Crtera Weght A Weght B Weght C Cost of Servce CST Fnancal Perforance FP Operatonal Perforance OP Reputaton of the 3PL RPT Long-ter Relatonshps LTR 0. 0.4 0.7 0. 0.6 0.05670 0.03308 0.00473 0.00000 0.0544 0.0386 0.0047 0.009 0.0764 0.00396 0.077 0.0475 0.0306 0.0347 0.0347 0.00000 0.0930 0.04990 0.00734 0.098 0.098 0.0057 0.03078 0.0796 0.059 0.05 0.006 0.0030 0.0754 0.0607 0.006 0.059 0.05 0.00000 0.055 0.0499 0.0050 0.0800 0.0050 0.00660 0.0680 0.00660 0.060 0.060 0.00480 0.00000 0.00000 0.03000 0.04 0.00435 0.04 0.0094 0.0094 0.00358 0.0036 0.0095 0.063 0.0036 0.0095 0.063 0.00000 0.0440 0.0440 5
A ethod for Selectng Thrd Party Logstc Servce Provder Usng Fuzzy an Crtera an Crtera Pont Weght A Weght B Weght C 0.0036 0.063 0.0095 TOTAL WEIGHT 0.7008 0.44398 0.38594 Table 4. Prorty weghts of an and sub-attrbutes and alternatves. 5. CONCLUSION Logstcs servce provder selecton process becoes ncreasngly portant n today s coplex envronent. The selecton process nvolves the deternaton of quanttatve and qualtatve factors to select the best possble provder. In ths study logstcs servce provder selecton va extent fuzzy has been proposed. The decson crtera are cost of servce fnancal perforance operatonal perforance reputaton of the 3PL and long-tern relatonshps. These crtera were evaluated to obtan the preference degree assocated wth each logstcs servce provder alternatve for selectng the ost approprate one for the copany. By the help of the extent fuzzy approach the abgutes nvolved n the data could be effectvely represented and processed to ake a ore effectve decson. As a result of ths study alternatve B s deterned as the best logstcs servce provder whch has the hghest prorty weght. The copany anageent found the applcaton and results satsfactory and decded to work wth alternatve B. For further research other fuzzy ult-crtera evaluaton ethods that have been recently proposed n a fuzzy envronent lke fuzzy TOPSIS or fuzzy outrankng ethods can be used and the obtaned results can be copared wth the ones found n ths paper. 5
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