Ranking Green Producers of Livestock and Poultry Feed by Using a Hybrid Fuzzy MADM Method

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1 Unversal Journal of Engneerng Scence 3(4): 64-78, 25 DOI:.389/ues Rankng Green Producers of Lvestock and Poultry Feed by Usng a Hybrd Fuzzy MADM Method Mehd Alnaghan,*, Mehrdad Karampour 2 Department of Industral and Systems Engneerng, Isfahan Unversty of Technology, Iran 2 Department of Industral Engneerng, Mazandaran Unversty of Scence and Technology, Iran Copyrght 25 by authors, all rghts reserved. Authors agree that ths artcle remans permanently open access under the terms of the Creatve Commons Attrbuton Lcense 4. Internatonal Lcense Abstract Supply chan management has ncreasngly attracted attenton as a systematc approach to ntegrate the supply chan n order to plannng and controllng the materals and nformaton from supplers to customers. Increasng mportance of envronmental ssues led to the creaton of a new concept called the Green supply chan management n the sphere of busness that s actually a combnaton of envronmental thought and as an ams to reduce the effects of supply chan manufacturng ndustres on the envronment. Suppler selecton s one of the most mportant ssues n green supply chan management. In ths paper, proper crtera are selected to evaluate the supplers n lvestock and poultry feed ndustry. Fuzzy Analytc Herarchy Process (AHP) and Fuzzy Technque for Order Preference by Smlarty to Ideal Soluton (TOPSIS) are used as a hybrd multple attrbute decson makng method to rank the supplers. Fnally proposed hybrd method and 6 crtera are appled to evaluate and rank three producers of lvestock and poultry feed n Isfahan state of Iran. Keywords Fuzzy TOPSIS. Introducton Suppler Selecton, GSCM, Fuzzy AHP, A supply chan management (SCM) s a system conssts of three key parts, whch are: the supply focuses on obtanng raw materals to manufacturng, the manufacturng focuses on convertng obtaned raw materals nto fnshed products and the dstrbuton focuses on reachng these fnshed products to customers through dstrbutors, warehouses and retalers. Supply chan actvtes begn wth customer orders and end wth customer satsfactons. Selecton of supplers plays a crtcal role n an organzaton because t heavly contrbutes to the overall performance of a supply chan system. Assessng supplers and selectng sutable ones among them a complex and crtcal decson makng problem due to consderng several crtera such as qualty, cost, servce, producton lead tme and envronmental mpact []. Envronmental ssues are no longer a concern only for envronmental experts. Envronmental awareness affects almost all parts of our socety and t s a specal concern for our ndustral sectors [2,3]. Companes and ther decson makers must consder envronmental ssues n all of ther admnstratve actvtes [4], ncludng the role of the supply chan [5] and the frms selecton of supplers [6]. The suppler selecton s a problem that companes face snce the begnnng of ts actvty. The choce of suppler/partner s one of the key factors for the operatonal success of many companes but also a tme and resource-consumng complex process. Today, many companes need to constantly strengthen ts compettveness through relable and effcent supply networks based on supplers/partners relatons n order to ncrease proft and promote customer value [7]. Suppler selecton s a key operatonal task for developng sustanable supply chan partnershps. Envronmental, socal, and economc dmensons must all be consdered n order to select a well-rounded sustanable suppler, one that can enhance supply chan performance. Part of the suppler selecton process nvolves suppler evaluaton together wth selecton, whch s an mportant ssue to supply chan and producton and operaton management lterature [8]. Envronmental sustanablty has ganed greater notorety amongst organzatons as ndustral envronmental mpacts resoundngly occur at local, regonal, and global levels. The ndustral response has not ust been reactve to these envronmental concerns, but has ncluded organzatonal search for compettve advantage [9,,,2,3,4]. These responses have also reverberated through organzatonal supply chans. One dmenson of ths mportant green supply chan response by organzatons s the ntroducton of green suppler development (GSD) programs. Integratng envronmental sustanablty nto suppler development has become a necessary measure for the long-term compettveness and operatons of focal companes and ther

2 Unversal Journal of Engneerng Scence 3(4): 64-78, supply chans [5,6,7,8]. The ntegraton of envronmental concerns wthn supply chan management has tself evolved nto a separate and growng feld. However, n order to mprove relatons wth the envronment, organzatons need to mplement strateges to reduce the envronmental mpacts of the entre supply chan durng the producton, consumpton, customer servce and dsposal of products [9,9]. Several envronmental crtera may be emphaszed when selectng the most envronmentally frendly supplers [2]. For example, several studes have suggested that the suppler selecton can be based on the crtera related to envronmental practces [2] or to hazardous materal management [22].Yan [23] s used AHP and genetc algorthm to evaluate supplers. Lee et al. [24] appled FAHP ntegrated wth the Delph method for green suppler evaluaton. Chen et al. [25] apply fuzzy set theory accompaned wth grey relatonal analyss for green suppler selecton. Kuo and Ln [26] proposed a method whch ntegrates ANP and DEA for green suppler evaluaton. In ths paper, a set of proper suppler selecton crtera n lvestock and poultry feed ndustry are gathered and also a hybrd Fuzzy MADM method s used to rank supplers that hold the vagueness n all steps of rankng procedure. Secton 2 ntroduces the fuzzy AHP and Fuzzy TOPSIS. The new approach of suppler assessment n lvestock and poultry feed ndustry s proposed n secton 3. New approach applcaton s presented n a case study n secton 4 and fnally secton 5 contans the concluson and some recommendatons for future researches. 2. Fuzzy AHP and Fuzzy TOPSIS Many process engneerng problems nvolve the selecton from a predefned set of alternatves, often usng multple, potentally conflctng crtera. Such cases requre the systematc use of Multple Attrbute Decson Makng (MADM) technques to provde a rgorous and ratonal approach to problem-solvng. In addton, ndustral applcatons also tend to requre the ntegraton of vewponts from multple decson makers, such as personnel nvolved n dfferent aspects of process engneerng (e.g., desgn, operaton mantenance). Thus, decson makng tends to become a complex task that requres the development of approprate process systems engneerng (PSE) tools. In partcular, MADM technques have been shown to be effectve for varous problems, such as reactor selecton [27], process dagnostcs [28] and rankng of sustanable process optons [29,3,3,32], among others Many MADM approaches ental the use of an aggregaton functon to derve a sngle composte score for each opton beng evaluated; varous technques make use of dfferent aggregaton phlosophes, often wth the ntegraton of subectve nputs from decson makers. 2.. Fuzzy AHP The Analytc Herarchy Process (AHP), orgnally developed by Saaty [33], s a theory of relatve measurement that provdes the analytcal tool to model the complexty of the problem and the process of the subectve and personal udgment of ndvduals or a group n decson makng. The underlyng phlosophy of AHP s to ntegrate subectvty wthn a rgorous mathematcal framework, rather than to try to elmnate t entrely from the decson-makng process. In practce, the AHP framework provdes a means of problem decomposton and structurng, so as to maxmze coherence of the subectve udgments (whch are usually elcted from doman experts). AHP has been wdely used as an MADM tool or weght estmaton technque n many areas of applcaton [34,35], such as energy plannng [36] and process safety assessment and desgn [37,38], among others. Fuzzy set theory was frst proposed as a means of representng ambguty by Zadeh [39], and was subsequently extended for general decson-makng applcatons by Bellman and Zadeh [4]. In partcular, fuzzy set theory has been used to enhance varous MADM technques to ncorporate uncertantes nherent n subectvty. Many such extensons are descrbed n Chen et al. [4]. In partcular, fuzzy AHP (FAHP) was frst proposed by Van Laarhoven and Pedrycz [42], who proposed to replace precse par wse comparsons wth Trangular Fuzzy Numbers (TFNs) and appled the fuzzy verson of the Logarthmc Least Squares Method (LLSM). In classcal AHP drectly the numercal values of lngustc varables are used for evaluaton of crtera. If the envronment where the decson makng process takes place s fuzzy, then fuzzy numbers are used for evaluaton concernng some devatons of decson makers. Nowadays, especally n complex economc condtons, many of the decsons are made n such an envronment. Thus, fuzzy verson of AHP or smlar method should be used n spte of ts complexty durng the calculatons [43]. Wthn the scope of ths study, a fuzzy AHP model wll be desgned for suppler selecton n Supply Chan Management. The soluton procedure of the fuzzy AHP approach nvolves sx essental steps as follows: Step. Defne the problem and state clearly the obectves and results Step 2. Decompose the complex problem nto a herarchcal sequental structure Step 3. Employ par-wse comparsons among decson elements and form comparson matrces wth fuzzy numbers Step 4. Use the extent analyss method to estmate the relatve weghts of the decson elements. Chang [44] proposed a fuzzy AHP approach based on the extent analyss method, whch s wdely used n suppler selecton problems [45,46]. Ths method uses lngustc varables to express the comparatve udgments gven by decson makers. Let X = { x,..., x,..., x n} represent an obect set and G = { g,..., g,..., gm} a goal set. In

3 66 Rankng Green Producers of Lvestock and Poultry Feed by Usng a Hybrd Fuzzy MADM Method the method proposed by Chang [44], each obect, x, s taken and extent analyss s performed for each goal, g. Thus, m extent analyss values for each obect can be obtaned, wth the followng sgns: m M,, M,..., M =,2,,n g g g g Where all the M ; (, 2,, m) = are trangular fuzzy numbers. The method follows the steps descrbed next. The value of fuzzy synthetc extent wth respect to the tth obect s defned as equaton (). To obtan m = m n m S = Mg Mg = = = M g (), perform the fuzzy addton operaton of m extent analyss values for a partcular matrx such as equaton (2). And to obtan = m m m m M g l, m, u = = = = (2) n m M g, perform the fuzzy = = addton operaton of M g value such as equaton (3). n m m m m M g l, m, u = = = = = = (3) And then compute the nverse of the vector above equaton (4). n m M g =,, (4) n n n = = u m l = = = As M = ( l,m,u) and M ( ) 2 = l2,m 2,u2 are two trangular fuzzy numbers, the degree of possblty of M 2 = ( l2,m 2,u 2) M = ( l,m,u) defned as equaton (5). ( 2 ) = sup y x mn ( (x), (y) M M ) V M M m m 2 (5) And can be equvalently express as equaton (6). V ( M 2 M ) = (6) l u2 ( m2 u2) ( m l) m l m 2 u 2 otherwse Accordng to fuzzy sets theory [39], the representaton of a fuzzy trangular number s gven n Fg. In Fg, d s the ordnate of the hghest ntersecton pont of D between µ M and µ M 2 to compare M and M 2. We need both V M M V M M. values of ( 2 ) and ( ) 2 Fgure. The ntersecton between possblty M and 2 M and ther degree of The degree possblty for a convex fuzzy number to be greater than k convex fuzzy M ; ( =, 2,, k ) numbers can be defned by equaton (7). V = (M M, M,, M ) 2 ( M M) and ( M M 2) and ( M M k ) ( M M ) k = V = mnv ; =, 2,, Assume that d ( A ) mnv ( S S ) k = for k k=, 2, 2, nk ; Then thw weght vector s gven by equaton (8). Where ' ( ' ( ) ' ( ) ', 2,, ( )) ( ) are n elements. T (7) W = d A d A 2 d A n (8) A ; =,2,,n Va normalzaton, the normalzed weght vectors are as equaton (9). T W = d ( A), d ( A2), 2, d ( A n ) (9) ( ) Where W s a crsp number. Step 5. Check the consstency of matrces to ensure that the udgments of decson makers are consstent. Step 6. Aggregate the relatve weghts of decson elements to obtan an overall ratng for the alternatves Fuzzy TOPSIS Hwang and Yoon [47] frst developed TOPSIS method. The man dea of TOPSIS s that the best alternatves should

4 Unversal Journal of Engneerng Scence 3(4): 64-78, have farthest dstance from the negatve deal soluton (NIS) and the shortest dstance from the postve deal soluton (PIS). Because a real world envronment s full of ambgutes, several researches have nvestgated MCDM problems wth fuzzy theory [48]. In ths case, the Fuzzy TOPSIS method, whch s one of the fuzzy MADM methods, could be appled as an effcent tool for the suppler selecton problem n supply chan system. Chen et al [49] used fuzzy TOPSIS method for suppler evaluaton and selecton n supply chan management. Boran et al [5] proposed TOPSIS method combned wth ntutonstc fuzzy set to select approprate suppler n group decson makng envronment. Snce crtera affectng suppler selecton problem are multdmensonal, they should be evaluated usng the TOPSIS n fuzzy envronment wth regards to more than one crteron as herarchcal to get more precse, consstent, and relable results. In general, fuzzy TOPSIS can solve MADM problems when herarchy s a three-layer model. Ths three-layer model ncludes goal, crtera (attrbutes), and alternatves. Kahraman [5] extended the fuzzy TOPSIS method to a herarchcal one named herarchcal fuzzy TOPSIS method that has ablty to handle the herarchy among the attrbutes and alternatves. Ths method nherts the herarchy mechansm of AHP method [52]. Ths method provdes greater superorty to classcal fuzzy TOPSIS methods [53]. Moreover, herarchcal fuzzy TOPSIS does not have dsadvantages of the parwse comparsons among crtera, sub crtera and alternatves. Therefore, ths research proposes the fuzzy herarchcal TOPSIS for suppler selecton and evaluaton n detergent producton ndustry, whch overcome dsadvantages of Chen s fuzzy TOPSIS [54] for normalzaton and determnng the fuzzy postve and negatve deal solutons. The soluton procedure of the fuzzy TOPSIS approach nvolves seven essental steps as follows: Step.The decson matrx s formed as equaton (). x x x n D = x x x n () xm xm x mn D s a m n matrx. m and n represent the number of s a trangular alternatve and attrbutes, respectvely. x x = l, m, u fuzzy number whch s shown as ( ) weghts are calculated as w = ( α, β, χ ).. Fuzzy Step 2. After obtanng decson matrx, t should be normalzed to make ts elements unt free. Normalze the fuzzy decson matrx usng lnear scale transformaton. The normalzed fuzzy decson matrx R s gven as = r m n equaton (). l m u r =,, and u + u u u = max u (beneft crtera) () l l l r =,, and l u m l = max l (cost crtera) Step 3. Compute the weghted normalzed decson matrx ( V ), by multplyng the weghtes of the evaluaton crtera ( w ) matrx,by to elements r of the normalzed fuzzy decson = v. Where v m n V s gven by v = r w. Step 4.Defne the fuzzy postve deal soluton ( A + ) the fuzzy negatve deal soluton ( ) + + {, +,, + A = v v v m} A = { v,,, v v m} Step 5.Compute the dstances alternatve from respectvely v + and equaton (3). and A, as equaton (2). d + and d (2) of each v accordng to n = (, n ) d dv( v, v ) d dv v v + + = = (3) = Where dd(.,. ) represent the dstance between two fuzzy numbers accordng to the vertex method. For trangular fuzzy numbers, ths s expressed as equaton (4) d( xz, ) = ( lx lz) + ( mx mz) + ( ux uz) 3 (4) Step 6. Compute the closeness coeffcent, C accordng to equaton (5). d C = + (5) d + d Step 7. Rankng the alternatves Accordng to descendng order of ranked. C all alternatves are

5 68 Rankng Green Producers of Lvestock and Poultry Feed by Usng a Hybrd Fuzzy MADM Method 3. Methodology Suppler selecton based on envronmental crtera has attracted the attenton of many nvestgators. The summary of the most cted artcles have been selected and lsted n Table that some of these crtera such as green product, cost, ISO 4 and etc. are common thus they are used n ths paper to form the herarchcal structure model. Table. Ten top cted artcle n green suppler selecton. Author(s) Ttle of artcle Suppler selecton crtera Mn and Galle [55] Green purchasng practces of US frms () Envronmental lablty and penalty (2) A suppler s envronmental commtment (3) Envronmental cost () Qualty (2) Technology capablty Lee et al. [24] A green suppler selecton model for hgh-tech (3) Polluton control ndustry. (4) Envronmental management (5) Green product (6) Green competences Jabbour and Jabbour [9] Kuo et al. [56] Wolf and Seurng [57] Yeh and Chuang [58] Buyukozkan and Cfc [59] Shaw et al. [6] Tseng and Chu [6] Jnus Roshandel et al. [62] Are suppler selecton crtera gong green? Case studes of companes n Brazl. Integraton of artfcal neural network and MADA methods for green suppler selecton. Envronmental mpacts as buyng crtera for thrd party logstcal servces. Usng mult-obectve genetc algorthm for partner selecton n green supply chan problems. A novel hybrd MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green supplers. Suppler selecton usng fuzzy AHP and fuzzy mult-obectve lnear programmng for developng low carbon supply chan. Evaluatng frm s green supply chan management n lngustc preferences. Selectng green supplers based on GSCM practces: Usng fuzzy TOPSIS appled to a Brazlan electroncs company. () Cost (2) Qualty (3) Innovaton (4) Delvery (5) Restrctons on the use of chemcals (6) ISO 4 () Qualty (2) Servce (3) Corporate socal responsblty (4) Delvery (5) Cost (6) Envronment () Cost (2) Lead tme (3) Relablty (4) Varety (5) Qualty (6) Envronment () Capablty (2) Productvty (3) Cost (4) Qualty (5) ISO 4 () Organzaton (2) Fnancal performance (3) Qualty (4) Technology (5) Corporatve socal and envronmental Responsblty () Cost (2) Qualty (3) Delvery (4) Emssons of greenhouse gases () Delvery (2) Fnancal performance (3) Relatonshp (4) Qualty (5) Prce (6) Green desgn (7) ISO 4 (8) Green purchasng (9) Cleaner producton () Qualty (2) Delvery (3)Cost/Prce (4) Technology (5) Flexblty (6) Responsveness & servces

6 Unversal Journal of Engneerng Scence 3(4): 64-78, The proposed approach nvolves sx essental steps as follows: Step : propose proper set of crtera Frst a long lst of crtera that are used for green suppler rankng n lterature s formed and then the modfcaton s done based on experts' opnons wth regard to the especal specfcatons of Lvestock and Poultry Feed ndustry. The 8 experts' opnons provde a short lst of crtera that contans 5 crtera (Green Concept, Fnance, Servces and Marketng, IT and qualty) and 6 sub-crtera (Green Educaton, Green Packagng, ISO 4 & OHSAS 8, Green Desgn & Manufacturng, The fnal Prce, Fnancal Status, Logstcs Costs, After sales Servce, Accountablty n Emergences, Market Share, R & D, Internet servces, Advertsng Informaton, The Qualty Management System and Certfcates of Qualty) for Green Producers of Lvestock and Poultry Feed Rankng problem. Sustanable packagng s a relatvely new addton to the envronmental consderatons for packagng. Envronmental educaton or green educaton refers to organzed efforts to teach how natural envronments functon, and partcularly, how human bengs can manage behavor and ecosystems to lve sustanably. It s a mult-dscplnary feld ntegratng dscplnes such as bology, chemstry, physcs, ecology, earth scence, atmospherc scence, mathematcs, and geography. The term often mples educaton wthn the school system, from prmary to post-secondary. However, t sometmes ncludes all efforts to educate the publc and other audences, ncludng prnt materals, webstes, meda campagns, etc. Sustanable desgn (also called envronmental desgn, envronmentally sustanable desgn, envronmentally conscous desgn, etc.) s the phlosophy of desgnng physcal obects, the bult envronment, and servces to comply wth the prncples of socal, economc, and ecologcal sustanablty and Green Manufacturng refers to reducng resource use, waste and emssons. ISO 4 s a seres of envronmental management standards developed and publshed by the Internatonal Organzaton for Standardzaton (ISO) for organzatons. The ISO 4 standards provde a gudelne or framework for organzatons that need to systematze and mprove ther envronmental management efforts. OHSAS 8, Occupatonal Health and Safety Management Systems Requrements (offcally BS OHSAS 8) s an nternatonally appled Brtsh Standard for occupatonal health and safety management systems. It exsts to help all knds of organzatons put n place demonstrably sound occupatonal health and safety performance. It s a wdely recognzed and popular occupatonal health and safety management system Step 2: propose herarchcal structure of problem Fgure 2 represents the herarchcal structure of Lvestock and Poultry Feed Rankng problem based on 8 experts' opnons. Step 3: propose fuzzy parwse comparson matrces Step 4: compute fuzzy weghts of each element n AHP Step 5: propose fuzzy decson matrces Step 6: use fuzzy TOPSIS to ranks alternatves

7 7 Rankng Green Producers of Lvestock and Poultry Feed by Usng a Hybrd Fuzzy MADM Method Fgure 2. Herarchcal structure of problem 4. Case Study The proper feed for lvestock and poultry has hgh mportance. Hence, n Isfahan provnce, lvestock and poultry breeders are lookng for the best suppler n ths ndustry. Three supplers of lvestock and poultry feed that called Khorak sazan espadan, Khorak dame koohpayeh and Sepahandaneh parsan are mentoned. These companes are ntroduced n follow. Khorak sazan espadan Co: Ths Company s started n 28 by gettng permsson from the Bureau of mnes and ndustres of Isfahan Provnce began to buld and launch n 2 and has begun to produce. The company n the feld of lvestock and poultry and aquaculture feed producton wth advanced devces, hgh technology and automatc systems. The products of company are dstrbuted n Iran. Khorak dame koohpayeh Co: Lvestock and poultry producton complex Foothlls proect started n 25 and ts frst phase was put nto operaton n 27. The complex specalsts and experts, and enoyng the best food formulas

8 Unversal Journal of Engneerng Scence 3(4): 64-78, 25 7 prepared wth the hghest qualty materals and nsttutons as well as havng advanced machnes to produce top qualty feed for lvestock and poultry n that order. The complex also has a bologcal and chemcal laboratores and a research farm wth a capacty of 4 thousand peces of chcken meat all raw materals and products n accordance wth the latest standards and assessments wll measure. Sepahandaneh parsan Co: The Sepahan Gran Corp n 25, backed by ten years n the ndustry wth the Anmal Plant scence n nutrton, health, GSI started ts actvtes. These companes on ther msson and sncere servce, nnovaton-orented scence, optmzaton of the producton cycle and fnally, the product s affordable and well bult. In ths context, strongest team of expert collaborators n the scentfc and R & D Specalst n Anmal Plant for the better of the followng servces have attempted to provde the followng servces: Innovaton n the producton of varous concentrates, feed supplements and Plant based on latest technology to acheve the hghest effcency n the anmal husbandry ndustry producton and Startup Manager, Qualty Engneerng (QE) system based on TQM and so on. To determne mportance of crtera and sub-crtera, a questonnare about status of three suppler n Esfahan s desgned and dstrbuted among 8 experts. After collectng experts s opnons, FAHP and FTOPSIS model are used to evaluate and select the best suppler. Fg 2 shows the proposed herarchcal structure. In ths fgure, the man obectve, crtera, sub-crtera, and alternatves are shown n the frst, second, thrd, and forth levels, respectvely. To determne degree of mportance for each maor crteron than the obectve, and also sub-crteron than the man crteron, Table 2a and 2b are used. Table 2a. Lngustc scales for mportance degree of each crteron and subcrteron Lngustc varables Full preferrence Very strong preference Strong preference Low preference Equal preference Trangular fuzzy number (7,9,) Table 2b. Lngustc scales for mportance degree of each crteron and subcrteron. Lngustc varables Yes No Trangular fuzzy number (,,) At frst, average of all expert s opnons s calculated and the parwse comparson matrces are formed whch shows n Tables 3-8. Table 3. The parwse comparson matrx. Goal Green Fnance Servces & Marketng IT Qualty Green (7,9,) Fnance Servces & Marketng IT (/9,/7,/5) (/,/9,/7) (/7,/5,/3) (/9,/7,/5) (/7,/5,/3) Qualty The above table says the green crtera are more mportant than the other crtera. Table 4. The parwse comparson matrx. Green Green Educaton Green Educaton Green Packagng ISO 4 ISO 4 & OHSAS (/7,/5,/3) Green Desgn & Manufacturng (/7,/5,/3) Green Packagng ISO 4 & OHSAS Green Desgn & Manufacturng The above table shows ISO 4 & OHSAS are more mportant than the other crtera. Table 5. The parwse comparson matrx. Fnance The fnal Prce Fnancal Status Logstcs Costs The fnal Prce Fnancal Status (/7,/5,/3) Logstcs Costs The above table says the fnal prce s more mportant than the other crtera.

9 72 Rankng Green Producers of Lvestock and Poultry Feed by Usng a Hybrd Fuzzy MADM Method Table 6. The parwse comparson matrx. Servces & Marketng After sales Servce Accountablty n Emergences Market Share After sales Servce (/7,/5,/3) Accountablty n Emergences (/7,/5,/3) Market Share The above table shows market share s more mportant than the other crtera. Table 7. The parwse comparson matrx. IT R & D Internet servces advertsng Informaton R & D Internet servces (/7,/5,/3) Advertsng Informaton The above table says R & D s more mportant than the other crtera. Table 8. The parwse comparson matrx. Qualty Product Sustanablty The Qualty Management System Certfcates of Qualty Product Sustanablty (/7,/5,/3) (/9,/7,/5) The Qualty Management System Certfcates of Qualty The above table shows certfcates of qualty are more mportant than the other crtera. There are 6 pared comparson matrces n the fnal level of the proposed AHP structure, as a sample, the pared comparson matrx of alternatves than one of the sub crteron has come n Table 9. Table 9. Fnal weghts of each sub crteron Green Educaton Alternatve Alternatve 2 Alternatve 3 Alternatve Alternatve 2 (/7,/5,/3) Alternatve 3 The fnal weght of each crteron s calculated by fuzzy multplyng weght of each sub-crteron than the crteron to the weght of crteron than the obectve. Results are ndcated n Table. Table. Fnal weghts of each sub crteron Green Educaton (.8,.287,.653) Green Packagng (.4,.779,.4872) ISO 4, OHSAS (.36,.64,.8526) Green Desgn (.24,.476,.738) The fnal Prce (.26,.638,.8268) Fnancal Status (.65,.26,.484) Logstcs Costs (.7,.78,.4452) After sales Servce (.5,.76,.483) Accountablty n Emergences (.24,.28,.323) Advertsng Informaton (.8,.9,.558) Market Share (.84,.554,.35) Product Sustanablty (.4,.33,.54) R & D (.4,.89,.92) The Qualty Management System (.36,.68,.324) Internet servces (.,.3,.96) Certfcates of Qualty (.224,.45,.54) The above table shows the green crtera are more mportant than the other crtera because they have more weghts. After calculatng the fnal weght of sub-crtera, accordng to expert decson matrx s formed that show n Table.

10 Unversal Journal of Engneerng Scence 3(4): 64-78, Table. Decson matrx. Sub-crteron Suppler Suppler 2 Suppler 3 G (7,9,) G2 G3 (,,) (,,) G4 (,,) (,,) F F2 F3 S S2 (7,9,) (7,9,) S3 (7,9,) I (,,) I2 (7,9,) I3 (7,9,) (7,9,) Q Q2 Q3 (7,9,) Table 2 and 3 shows normalzed decson matrx and normalzed weghted decson matrx respectvely. Table 2. Normalzed decson matrx Sub-crteron Suppler Suppler 2 Suppler 3 G (5/,7/,9/) (5/,7/,9/) (7/,9/,) G2 (5/9,7/9,) G3 (,,) (,,) G4 (,,) (,,) F (3/9,3/7,3/5) (3/9,3/7,3/5) (3/7,3/5,3/3) F2 (5/9,7/9,) F3 (3/9,3/7,3/5) (3/9,3/7,3/5) (3/7,3/5,3/3) S (5/9,7/9,) (5/9,7/9,) S2 (7/,9/,) (5/,7/,9/) (7/,9/,) S3 (7/,9/,) (5/,7/,9/) (5/,7/,9/) I (,,) I2 (5/,7/,9/) (/,3/,5/) (7/,9/,) I3 (7/,9/,) (5/,7/,9/) (7/,9/,) Q (5/9,7/9,) (5/9,7/9,) Q2 (5/9,7/9,) Q3 (5/,7/,9/) (5/,7/,9/) (7/,9/,) Table 3. Normalzed weghted decson matrx. Sub-crteron Suppler Suppler 2 Suppler 3 G (.4,.8,.35) (.4,.8,.35) (.5,.23,.7) G2 (.5,.43,.379) (.5,.43,.379) (.8,.6,.48) G3 (,,) (,,) (.36,.64,.853) G4 (,,) (,,) (.24,.48,.73) F (.9,.7,.496) (.9,.7,.496) (.,.98,.827) F2 (.4,.2,.48) (.2,.4,.5) (.2,.4,.5) F3 (.4,.33,.267) (.4,.33,.267) (.5,.47,.445) S (.,.6,.48) (.,.4,.38) (.,.6,.48) S2 (.2,.8,.32) (.,.3,.8) (.2,.8,.32) S3 (.5,.45,.35) (.4,.35,.258) (.4,.35,.258) I (.4,.9,.9) (,,) (.4,.9,.9) I2 (,.2,.6) (,.,.9) (.,.2,.2) I3 (.,.7,.59) (,.6,.48) (.,.7,.59) Q (.2,.,.5) (.,.7,.4) (.2,.,.5) Q2 (.5,.22,.236) (.5,.22,.236) (.8,.32,.32) Q3 (.,.67,.42) (.,.67,.42) (.4,.86,.54) Tables 4 and 5 show values for dstance of each alternatve from postve and negatve deal solutons.

11 74 Rankng Green Producers of Lvestock and Poultry Feed by Usng a Hybrd Fuzzy MADM Method Table4. Dstance of each alternatve from the postve deal soluton. Alternatves Suppler Suppler 2 Suppler 3 Alternatves Suppler Suppler 2 Suppler 3 Crtera G.8.8 Crtera S2.4 G S G3.5.5 I.64 G I2.2.6 F.97 I3.6 F2.9.9 Q.6 F3.3 Q S.6 Q Table 5. Dstance of each alternatve from the negatve deal soluton. Alternatves Suppler Suppler 2 Suppler 3 Alternatves Suppler Suppler 2 Suppler 3 Crtera G.8 Crtera S2.4 G2.63 S3.33 G3.5 I G4.43 I2.4.6 F I3.6.6 F2.9 Q.6.6 F3.3.3 Q2.39 S.6.6 Q3.54 Table 6 shows summaton of dstances of each alternatve from postve and negatve deal solutons calculated usng Tables 4 and 5. Table 6. Summaton of dstance of each alternatve from negatve and postve deal solutons. Alternatve Suppler Suppler 2 Suppler 3 From the postve deal soluton (d + ) From the negatve deal soluton (d ) The above table shows suppler 3 has the most dstance from the negatve deal soluton and the shortest dcance from the postve deal soluton between all of supplers. Table 7 shows the fnal results of the propose method as follows: Results of rankng the supplers n FTOPSIS show that the suppler3 (Sepahandaneh parsan co.) s the best suppler of lvestock o poultry feed. Also, suppler2 (Khorakdame koohpayeh co.) s selected as the worst ranked suppler. Table 7. Fnal results of the FTOPSIS method as follows. Alternatve C Rank Khorak sazan espadan Co Khorak dame koohpayeh Co.92 3 Sepahandaneh parsan Co Conclusons Organzatons always try to produce affordable better qualty products wth lower cost by standardzng and mprovng ther nternal processes n order to ncrease ther compettve strength. Ths days green concept s added to Supply chan management. Recognton of green ndustres and producton of eco-frendly products n cooperaton wth supplers, s commtted to envronmental ssues (green suppler ssue) for the manufacturers. It s very mportant that ths ssue has led to the development of the concept of green supply chan management (GSCM) have been n the ndustry. Present research amed to evaluated producers of feed for growng lvestock and poultry n Esfahan provnce. Three supplers were evaluated accordng to 6 crtera. The crtera were grouped nto fve classes of green, fnance, IT, servces and marketng and qualty n a herarchcal structure. Then, the fuzzy weghts of each crtera s computed and fuzzy TOPSIS method was used to compare supplers accordng to crtera. Results showed that suppler 3 by C equvalent.774 was the best suppler. Also, suppler by C equvalent.284 and suppler 2 by C equvalent.92 were ranked as the second, thrd places, respectvely; In fact, supplers 3 wth a producton of envronmentally frendly, green packagng, envronmental tranng, certfcatons related to envronmental and other crtera and mplement them, s selected as the best suppler. As a result of the emprcal study n lvestock and poultry ndustry, we found that the ntegraton of Fuzzy AHP and fuzzy TOPSIS was a practcal and effcent tool for rankng canddate supplers n terms of ther overall performance wth respect to multple crtera; Because the mpact of varous crtera such as prce, qualty, envronmental

12 Unversal Journal of Engneerng Scence 3(4): 64-78, compatblty and etc. due to ther factor are well understood. Usng fuzzy theory for suppler selecton and evaluaton problem can reduce ambgutes and vagueness that are nherent n the feld of suppler selecton management decson problems. Fnally, an experment has been conducted to apply the proposed methodology for solvng green suppler selecton problems satsfactory. For the extenson of ths study, fuzzy ANP and fuzzy DEMATEL method whch are able to consder some nner and outer dependences and causal relatonshp among crtera or alternatves can be appled. Future researches could apply the proposed methodology to develop a fuzzy group decson support system to determne polcy makng n green suppler selecton management decson problems. Appendx Ths questonnare has been formed to consder the vews of experts then ts results are used to form the herarchcal structure model. The fnancal condton of the producers n recent years 2. The fnancal condton of the producers n recent years 3. Logstcs costs Too much Much Mddle Low Too low 4. Fnal prce of products Too much Much Mddle Low Too low 5. The percentage of on-tme delvery Too much Much Mddle Low Too low 6. The average delvery perod Too much Much Mddle Low Too low 7. In response to customer demand n an emergency 8. The effort to create awareness and tranng of personnel n order to protect the envronment 9. The envronmental compatblty of equpment and facltes. Havng an envronmental certfcaton such as Iso 4 and OHSAS Yes No

13 76 Rankng Green Producers of Lvestock and Poultry Feed by Usng a Hybrd Fuzzy MADM Method. The approprateness of the desgn and producton of envronmentally frendly Too much Much Mddle Low Too low 2. The proporton of the company wth the requrements of envronmental certfcatons Too much Much Mddle Low Too low 3. The use of envronmentally frendly materals n packagng Too much Much Mddle Low Too low 4. The percentage of waste Too much Much Mddle Low Too low 5.The durable of the products Too much Much Mddle Low Too low 6. The approprateness of operaton and qualty certfcates Too much Much Mddle Low Too low 7. Whch qualty certfcates does the company have? 8. How the company mplement the qualty management system 9. Is there R & D n company? 2. Company status n regard to the approprate server network and the Internet 2. Company status of Automaton 22. Is there any schedule for backup data? Yes No 23. Is there any network securty software? Yes No 24. The staff use of IT tools Too much Much Mddle Low Too low

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