Sustainable and Resilient Garment Supply Chain Network Design with Fuzzy Multi-Objectives under Uncertainty

Transcription

1 susanably Arcle Susanable and Reslen Garmen Supply Chan Newor Desgn wh Fuzzy Mul-Obecves under Uncerany Sona Irshad Mar 1,, Young Hae Lee 1 and Muhammad Saad Memon 1,, * 1 Deparmen of Indusral and Managemen Engneerng, Hanyang Unversy, Ansan 15588, Korea; sona.rshad@faculy.mue.edu.p S.I.M.); yhlee@hanyang.ac.r Y.H.L.) Deparmen of Indusral Engneerng and Managemen, Mehran Unversy, Jamshoro 7606, Pasan * Correspondence: saad.memon@faculy.mue.edu.p; Tel.: Academc Edor: Marc A. Rosen Receved: 1 June 016; Acceped: 10 Ocober 016; Publshed: 16 Ocober 016 Absrac: Researchers and praconers are ang more neres n developng susanable garmen supply chans n recen mes. On he oher hand, he supply chan manager drops susanably obecves whle copng wh unexpeced naural and man-made dsrupon rss. Hence, supply chan managers are now ryng o develop susanable supply chans ha are smulaneously reslen enough o cope wh dsrupon rss. Owng o he mporance of he consdered ssue, hs sudy proposed a newor opmzaon model for a susanable and reslen supply chan newor by consderng susanably va emboded carbon fooprns and carbon emssons and reslence by consderng reslence ndex. In hs paper, nally, a possblsc fuzzy mul-obecve susanable and reslen supply chan newor model s developed for he garmen ndusry consderng economc, susanable, and reslence obecves. Secondly, a possblsc fuzzy lngusc wegh-based neracve soluon mehod s proposed. Fnally, a numercal case example s presened o show he applcably of he proposed model and soluon mehodology. Keywords: susanable supply chan; reslen supply chan; dsrupon rss; possblsc fuzzy opmzaon; mul-obecve opmzaon 1. Inroducon and Leraure Revew The exle and garmen supply chan nvolves several envronmenal ssues, ncludng hazardous polluans and wase managemen pracces. The garmen ndusry s envronmenally unfrendly due o hazardous polluans such as dyeng chemcals and carbon doxde emssons durng producon and ransporaons. Today, hese ssues are beng addressed by compulsory carbon fooprn axes on exle producs, susanably rules and gudelnes, Inernaonal Organzaon for Sandardzaon ISO) cerfcaon, and emergng rends for corporae socal responsbly [1]. Susanably s no he only prmary focus of supply chan o ncrease her performance, bu he rend shows ha susanably s gong o be sandard n he near fuure. On he oher hand, unceran dsrupon rss assocaed wh supply chans hnder an mplemenaon of he susanably obecve. Many auhors have proposed varous supply chan rs managemen sraeges o mnmze he mpac of dsrupon rss. Among hem, reslence s a new approach o desgn supply chan newors []. The mos wdely used defnon of supply chan reslence, proposed by Chrsopher and Pec [3], s he ably of a sysem o whsand and reurn o s orgnal or desred) sae afer beng dsruped. Pe, e al. [] explaned ha reslence faclaes a supply chan o reurn s orgnal performance afer dsrupons, preparng for unexpeced evens, and respondng o dsrupons. Mar, e al. [5] defned supply chan reslence as a mehod o reduce he severy and lelhood of supply chan dsrupon rss. Susanably 016, 8, 1038; do: /su

2 Susanably 016, 8, 1038 of Despe he mporance of reslence and susanable supply chan desgn, very few sudes are avalable n he leraure ha only dscusses reslence and susanably ssues n a supply chan conex. Accordng o Rose [6], he exreme dsrupons could badly affec he envronmen, whch dsrups he maor acves of supply chans. The maor barrer n developng he susanable supply chan newor s uncerany assocaed wh supply chan acves. Therefore, a susanable supply chan should be reslen and flexble enough o cope wh unceran dsrupons [7]. Ths requred o buld susanable supply chans whch are smulaneously reslen, agle, and lean o cope wh unceran dsrupon such as naural or man-made dsasers [8]. Recenly, Azevedo, e al. [9] dscussed he mporance of green and reslen supply chan managemen pracces n he auomove supply chan. They showed ha he reslen paradgm s consdered more mporan han he green paradgm due o s compeve advanage. The oher reason s ha green pracces are mposed exernally and s oblgaory. Govndan, e al. [10] dscussed he lnage of lean, agle, green and reslen pracces. Research showed ha lean, agle, green, and reslence pracces are mporan for auomove ndusry due o her ndvdual compeve advanages. Mar, Lee and Memon [] proposed newor opmzaon model whch smulaneously consdered boh susanably and reslence of he supply chan. They developed a mul-obecve newor opmzaon model based on goal programmng whch consders economc, susanable, and reslence obecves. Dsrupon of he supply chan newor leads o supply uncerany and s mporan o susanable supply chan performance. Frms ry o fnd alernae soluons o cope wh dsruped supply and mgh lose susanably arges. Therefore, s mporan o consder an unceran envronmen n he desgn of susanable and reslen supply chan newors. The above dscusson shows ha susanably s becomng a prmary focus of supply chans and reslence s a necessy o acheve he susanably arges. Thus, frms should fnd a beer way o manage her resources whle copng wh unexpeced dsrupon rss. Keepng n vew he saed problem, hs sudy proposes an negraed susanable and reslen supply chan newor consderng dsrupon rss. To do so, hs arcle proposes mul-obecve susanable and reslen supply chan opmzaon model for he garmen ndusry by consderng sochasc and recognve unceranes. In he garmen ndusry, here are sgnfcan opporunes o ncrease susanably by mang effecve producon and ransporaon decsons whch are drecly relaed o envronmenal emssons [1]. Addonally, hs sudy consders an expeced dsrupon cos obecve as a reslence merc o esmae locaon-specfc rss. Expeced dsrupon cos s a merc for evaluang he reslence of supply chan and defned as a loss of opporuny cos due o no meeng he demand on me durng dsrupon rss [11]. The lelhood of dsrupon rss a poenal locaons of supplers, manufacurng facles, and collecon cener s esmaed usng he Reslence Index RI) proposed by FMGlobal [1]. The Reslence Index s a daa-drven ool o evaluae he rss nheren n he counry based on nne ey drvers of supply chan rss.e., GDP per capa, Polcal rss, ol nensy, exposure o naural hazards, qualy of rs managemen, qualy of fre managemen, corrupon conrol, nfrasrucure, and local suppler qualy). RI s bound o scale from 0 o 100 represenng he lowes o hghes reslence. Furhermore, for he frs me, hs sudy consders he reverse supply chan newor desgn n buldng reslence due o s mporance n susanable supply chan. To he bes of auhors nowledge, hs research s one of he prmary wors usng possblsc programmng approach for a susanable and reslen supply chan newor desgn under sochasc and recognve unceranes and he leraure consderng hs approach n susanable supply chan newor desgn s sll scarce.. Mahemacal Model As dscussed earler, he focus of hs research s o desgn he garmen supply chan newor based on he rple radeoffs of economc, susanable, and reslen obecves. Thus, he problem ncludes mul-obecve opmzaon model ha should gve compromse soluon based on DMs preferences.

3 Susanably 016, 8, of The problem s srucured as a supply chan newor see Fgure 1) conssng of a se of supplers s), from Susanably whch 016, varous 8, 1038 raw maerals are purchased by a se of manufacurng facles ), 3 of where 3 he produc s manufacured and dsrbued o varous cusomer zones ). Collecon ceners ) are produc s manufacured and dsrbued o varous cusomer zones ). Collecon ceners ) are requred o be opened o collec and process used producs. The used producs are hen sen o eher requred o be opened o collec and process used producs. The used producs are hen sen o eher resale mares l) for sellng or donang no poor counres, reclamaon mlls m) or flocng ndusry resale mares l) for sellng or donang no poor counres, reclamaon mlls m) or flocng n) o recycle he used producs ha are no reusable. ndusry n) o recycle he used producs ha are no reusable. sm Q s mc Q Suppler s Manufacurng facly Cusomer zone crm Q m cc Q Exsng fber reclamaon cener m Exsng flocng ndusry n cf Q n cm Q l Collecon Cener Exsng resale mare l Reverse Flow Forward Flow Fgure Fgure Supply chan newor under consderaon. Afer desgnng he srucure of he supply chan problem, a mul-obecve mxed neger lnear programmng Afer desgnng MOMILP) he srucure model of s he presened. supply chan The model problem, consss a mul-obecve of hree obecve mxed funcons neger and lnear programmng consrans MOMILP) relaed o he model garmen s presened. supply chan The newor modelunder consss consderaon. of hree obecve The noaons funcons and and consrans esmaons relaed of obecve o he funcons garmen and supply consrans chan newor are dscussed under below. consderaon. The noaons and esmaons of obecve funcons and consrans are dscussed below..1. Model Noaons.1. Model Noaons Indces Index of poenal locaon for manufacurng facles = 1,,, I Indces Index of exsng cusomer zones = 1,,, J Index Index of of poenal locaons locaon for collecon manufacurng ceners facles = 1,,, = K 1,,..., I l Index of of exsng cusomer mares o zones sale reusable = 1,, exle..., Jl = 1,,, L m Index of of poenal exsng fber locaons reclamaon for collecon mlls m = ceners 1,,, M = 1,,..., K l n Index of exsng mares flocng ndusry o sale reusable n = 1,,, exle N l = 1,,..., L m s Index of of exsng fber supplers reclamaon s = 1,,, mlls S m = 1,,..., M n Index of of exsng me perod flocng = 1,, ndusry, T n = 1,,..., N s Parameers d Index of exsng supplers s = 1,,..., S Index Demand of me for new perod produc = 1, a, cusomer..., T zone n perod uns/perod) Parameers p Prce of new produc n perod $/un/perod) d Demand Percenage forof new producs produc recovered a cusomer from cusomer zone nzone perod n uns/perod) p a Prce Cos of new nsallng produc manufacurng perod facly $/un/perod) $) ψ b Percenage Cos of nsallng of producs collecon recovered cener from $) cusomer zone n perod ã Cos Transporaon of nsallng cos manufacurng per un from suppler facly s $) o manufacurng facly n perod c s b Cos $/un/perod) of nsallng collecon cener $)

4 Susanably 016, 8, 1038 of Parameers c s ẽ f g l hm õ n ce em f s ce man ce sm s ce mc ce cc ce cm l ce cr m ce c f n ce pcc ce prm m ce p f n π s β χ ε m φ n ϕ γ η m λ n ν s p sd s p md p cd Transporaon cos per un from suppler s o manufacurng facly n perod $/un/perod) Transporaon cos per un from manufacurng facly o cusomer zone n perod $/un/perod) Transporaon cos per un from cusomer zone o collecon cener n perod $/un/perod) Transporaon cos per un from collecon cener o resale mare l n perod $/un/perod) Transporaon cos per un from collecon cener o fber reclamaon mll m n perod $/un/perod) Transporaon cos per un from collecon cener o flocng ndusry n n perod $/un/perod) Emboded carbon fooprns of maeral comng from suppler s n perod KgCO /un/perod) Carbon emsson durng producon of un produc a manufacurng facly n perod KgCO /un/perod) Carbon emsson for shppng un produc from suppler s o manufacurng facly n perod KgCO /un/perod) Carbon emsson for shppng un produc from manufacurng facly o cusomer zone n perod KgCO /un/perod) Carbon emsson for shppng un produc from cusomer zone o collecon cener n perod KgCO /un/perod) Carbon emsson for shppng un produc from collecon cener o resale mare l n perod KgCO /un/perod) Carbon emsson for shppng un produc from collecon cener o fber reclamaon mll m n perod KgCO /un/perod) Carbon emsson for shppng un produc from collecon cener o flocng ndusry n n perod KgCO /un/perod) Carbon emsson durng processng un produc a collecon cener n perod KgCO /un/perod) Carbon emsson durng processng un produc a fber reclamaon mll m n perod KgCO /un/perod) Carbon emsson durng processng un produc a flocng ndusry n n perod KgCO /un/perod) Un purchase cos of maeral from suppler s n perod $/un/perod) Manufacurng cos per produc a manufacurng facly n perod $/un/perod) Processng cos per produc a collecon cener n perod $/un/perod) Processng cos per produc a fber reclamaon mll m n perod $/un/perod) Processng cos per produc a flocng ndusry n n perod $/un/perod) Capacy of manufacurng facly n perod uns/perod) Capacy of collecon cener n perod uns/perod) Capacy of fber reclamaon mll m n perod uns/perod) Capacy of flocng ndusry n n perod uns/perod) Capacy of suppler s n perod uns/perod) Probably of dsrupon rs a suppler s n perod Probably of dsrupon rs a manufacurng facly n perod Probably of dsrupon rs a collecon cener n perod

5 Susanably 016, 8, of Decson Varables Q SM Transporaon quany from suppler s o manufacurng facly n perod s uns/perod) Q MC Transporaon quany from manufacurng facly o cusomer zone n perod uns/perod) Q cc Transporaon quany from cusomer zone o collecon cener n perod uns/perod) Q cm Transporaon quany from collecon cener o resale mare l n perod l uns/perod) Q crm Transporaon quany from collecon cener o fber reclamaon mll m n m perod uns/perod) Q c f Transporaon quany from collecon cener o flocng ndusry n n perod n uns/perod) { x = { y = If a manufacurng facly s open 1, oherwse 0 If a collecon cener s open 1, oherwse 0.. Formulaon of Obecve Funcons The obecve of he proposed susanable and reslen supply chan model s o mnmze he oal supply chan cos, mnmze carbon emsson, and mnmze expeced dsrupon cos n all consdered perods. Frs, obecve funcon f cos n Equaon 1) mnmzes he oal cos of supply chan. Second, obecve funcon f sus n Equaon ) mnmzes he oal carbon emsson. Thrd, obecve funcon f edc n Equaon 3) mnmzes expeced dsrupon cos. Varous esmaons relaed o hese obecves are dscussed n below secon. Obecve 1: Mnmze f cos x) = Toal supply chan cos 1) Obecve : Obecve 3: Mnmze f sus x) = Toal carbon emsson ) Mnmze f edc x) = Expeced dsrupon cos 3) a. Toal supply chan cos Economc obecve) Varous coss assocaed wh he supply chan are calculaed n Equaon ). The frs wo erms represen he nsallaon cos of manufacurng facles and collecon ceners, respecvely. The remanng erms represen he maeral purchasng cos, producon cos, and processng coss for supplers, manufacurng facles, collecon ceners, fber reclamaon cener, and flocng ndusres along wh correspondng ransporaon coss n all perods, respecvely. ã x + b y + s l g l Q cm l + Toal supply chan cos = + π s + c s )Q SM s ε m + h m )Q crm m + m β + ẽ )Q mc + φ n + n )Q c f n n χ + f )Q cc + ) b. Toal Carbon emsson Susanable obecve) Varous carbon emssons n he supply chan are compued n Equaon 5). The frs erm esmaes emboded carbon fooprns and carbon emsson durng ransporaon of maeral comng from varous supplers. I s very mporan o mnmze he emboded carbon fooprn of he procured

6 Susanably 016, 8, of maeral n order o consder every aspec of susanable supply chan. For nsance, f he manufacurer un avalable n hghly green zone procured raw maeral wh a hgh carbon emboded fooprn, wll fal o aan s susanably obecve and may face legal resrcon because of beng n he green zone. Second erm ncludes carbon emsson durng producon and ransporaon of produc o cusomer zones. Thrd erm ncludes carbon emsson durng processes and collecon ceners and ransporaon of used producs. Fourh erm ncludes carbon emsson durng ransporaon of used producs o resale mares. The las wo erms nclude carbon emsson durng recyclng processes and ransporaon of used producs from collecon ceners o recyclng ceners. s ce em f s + ces sm)qsm s + l cel cmqcm l + Toal carbon emsson = ce man + ce mc )Q mc + ce c f m + ceprm m )Q crm m + m ce cc + cepcc )Q cc + ce c f n + cep f n )Qc f n n 5) c. Expeced dsrupon cos Reslence obecve) The goal of hs obecve s o mnmze expeced dsrupon cos due o any dsrupon rs assocaed wh any member of he supply chan n all perods. In hs research, only he forward supply chan s consdered o measure he reslence obecve snce he forward supply chan reslency s more mporan and also has an mpac on he reverse supply chan. Hence, Equaon 6) measures he expeced dsrupon cos due o dsrupon of he suppler, manufacurng facles, and collecon ceners n all perods. Expeced dsrupon cos =.3. Formulaon of Consrans s p sd s Q sm s + p md Q mc + ) p cd Qcc p 6) Consrans 7) 11) are capacy resrcons on suppler, manufacurng facles, collecon cener, fber reclamaon mll, and flocng ndusry, respecvely, n all perods. In addon, Consrans 8) and 9) ensure ha he producs are produced and processed only on exsng manufacurng facles and collecon ceners respecvely n all perods. s Q sm s ν s, 7) Q mc x ϕ, 8) Q cc y γ, 9) Q crm m η m, 10) m Q c f n λ n, 11) n Consran 1) promses ha he amoun of producs ranspored from manufacurng facles o cusomer zone should sasfy s demand. Consran 13) shows ha all he used producs are colleced from cusomer zones. Q mc d, 1) Q cc ψ d, 13)

7 Susanably 016, 8, of Consran 1) balances he npu and oupu of he maeral n a manufacurng facly. The amoun of ncomng maeral from supplers o he manufacurng facly s equal o a number of ougong producs from he manufacurng facly o he cusomer zone. Smlarly, Consrans 15) 17) balance he npu and oupu of used producs n he collecon cener. The ncomng used producs from cusomer zones are eher sen o resale mares or separaed for fber reclamaon process and flocng process. I s assumed n hs sudy ha 50% of colleced producs are reusable, and he remanng producs are hen separaed for reclamaon and flocng processes. Accordng o U.K. ndusry sources, abou 50 percen of colleced exle ems can be reused and he remanng 50 percen can recycled [13]. Q cc s = Q sm Q cm l Q cm l s = l + l = 0.5 Q crm m m = Q mc, 1) Q crm m n m + n Q c f n, 15) Q cc, 16) Q c f n, 17) Consrans 18) and 19) mpose non-negavy and bnary resrcons o all he correspondng decson varables, respecvely. 3. Proposed Soluon Mehodology Q sm s, Qmc, Qcc, Qcm l, Qcrm m, Qc f n 0,,,, l, m, n, s, 18) x, y {0, 1},, 19) Several soluon mehodologes are developed o solve he mul-obecve programmng models. Fuzzy-based programmng echnques are hghly used n hs area because of her capably n esmaon and adusmen of he decson maer s sasfacon level of each obecve explcly [1]. In hs sudy, nally, he mehodology proposed by Jménez, e al. [15] s appled o conver he unceran model no an equvalen auxlary crsp model. The proposed unceran model n prevous secon assumes possblsc fuzzy parameers. Then he neracve fuzzy wegh, based soluon mehodology, s developed o solve he proposed susanable and reslen supply chan model. The seps of he proposed soluon mehodology are summarzed as follows: Sep 1. Conver fuzzy mul-obecve model no equvalen auxlary crsp model In hs sage, he proposed mul-obecve model s convered no an equvalen auxlary crsp model. Jménez, Arenas, Blbao and Rodrı [15] mehod used n hs sudy due o: ) s srong mahemacal formaon whch s based on expeced nerval and expeced value of fuzzy numbers o deal wh unceran parameers; and ) s suppor of any fuzzy membershp funcon such as rapezodal and rangular wh eher symmerc or asymmerc forms. Readers can refer Jménez, Arenas, Blbao and Rodrı [15] for deal nformaon on hs mehod. Assume ha ϑ s a rangular fuzzy number, hen he membershp funcon of ϑ can be defned as n Equaon 0), where pes s he pessmsc value, mos s he mos lely value, and op s he opmsc value of rangular fuzzy number. f ϑ x) = ϑ mos x ϑpes ϑ pes f ϑ pes x ϑ mos µ ϑ x) = 1 f x = ϑ mos g ϑ x) = ϑop x ϑ op f ϑ mos x ϑ op ϑ mos 0 f x ϑ pes or x ϑ op 0)

8 Susanably 016, 8, of Accordng o Jménez, Arenas, Blbao and Rodrı [15], he expeced nerval EI) and expeced value EV) of rangular fuzzy number ϑ can be defned as follows. EI ϑ) = [E ϑ 1, Eϑ ] = f 1 ϑ x)dx, 0 g 1 ϑ EV ϑ) = Eϑ 1 + Eϑ 1 x)dx, = [ 1 ϑpes + ϑ mos ), 1 ] ϑmos + ϑ op ) = ϑpes + ϑ mos + ϑ op Consequenly, usng he defnon of expeced nerval and expeced value of a fuzzy number, he equvalen auxlary crsp model of a proposed possblsc susanable and reslen supply chan model can be formulaed as follows. The unceran obecve funcons are convered no crsp forms usng expeced value defnon. In addon, he unceran consrans wll be convered no equvalen crsp forms usng expeced nerval defnon. Where, α represens he confdence level. The decson maers can choose level of confdence based on avalable nformaon and her percepon. Addonally, decson maers can vary value of α n order o generae dfferen radeoff soluons. In hs formulaon, α = 0.5 means ha he mos lely values of parameers are preferred, whereas α < 0.5 means model parameer values are beween pessmsc and mos lely values. Smlarly, α > 0.5 means ha value of model parameers are beween mos lely and pessmsc values. 1) ) apes s +a mos πpes s Mnmze f cos x) = +a op bpes +b mos +b op +π op s +c pes s +cmos s +c op s )Q sm s + )x + βpes χpes +π mos s +β mos +β op +e pes )y + +emos +e op )Q mc+ +χ mos +χ op + f pes + f mos + f op )Q cc + l gpes εpes m +εmos m +εop m φpes n l +gmos l +gop l )Q cm l + m +hpes m +hmos m +hop m )Q crm m + n +φmos n +φ op m +pes n +mos n +op n )Q c f n 3) s Mnmze f sus x) = ce em f s + ces sm)qsm s + Mnmze f edc x) = Subec o s ce cc + cepcc )Q cc + ce c f m + ceprm m )Q crm m + m s Q sm s [α ν pes s p sd.pes s p md.pes p cd.pes +p sd.mos s +p md.mos +p cd.mos ce man + ce mc )Q mc+ l cel cmqcm l + ce c f n + cep f n )Qc f n n ) +p sd.op s +p md.op +p cd.op Q sm s + ) Q mc+ ) Q cc ) + νs mos νs mos + 1 α) p pes +p pes +p op ) ) 5) + ν op )] s, 6)

9 Susanably 016, 8, of [ pes ϕ Q mc x α [ Q cc [α Q cc y α Q crm m [α m Q c f n [α n Q mc ψ mos +ψ op α γ pes η pes m + ηmos m λ pes n dmos ) + 1 α) Sep. Oban effcen α-exreme soluons ) + ϕ mos ϕ mos + 1 α) ) + γ mos γ mos + 1 α) + λ mos n + d op ψ pes ) ) +ψ mos Q sm s = s + ϕ op )], 7) + γ op )], 8) ηm mos + η op )] m + 1 α), 9) λ mos n + λ op )] n + 1 α), 30) + 1 α) )] [ α Q cc = Q cm l + Q crm m + l m Q cm l = 0.5 l Q crm m = m d mos d pes +d op + d mos ), 31) ) + 1 α) d pes +d mos )], 3) Q mc, 33) Q c f n, 3) n Q cc, 35) Q c f n, 36) n Q sm s, Qmc, Qcc, Qcm l, Qcrm m, Qc f n 0,,,, l, m, n, s, 37) x, y {0, 1},, 38) Usually, wo mehods are used n pracce o fnd ou effcen α-exreme soluons. In he frs mehod, he DMs are encouraged o sugges he bounds on each obecve. However, hs mehod s less common because s dffcul for DMs o sugges bounds when he problem s of large scale. The second mehod ha we used n hs sudy s o fnd an exreme possble soluon by solvng each obecve separaely. In hs sep, he crsp model s solved consderng one obecve along wh consrans n a sngle run. Ths resuls n lower α-lb) and upper α-ub) bounds on each obecve funcon. Sep 3. Deermne he Fuzzy membershp funcon for each obecve The payoff values.e., α-lb and α-ub) are now used o develop he fuzzy membershp funcon for each obecve of proposed model. Assumng ha membershp funcons based on preference or sasfacon are lnear, he lnear membershp for fuzzy obecves s gven as follows: 0, f cos > fcos α UB fcos µ cos x) = α UB f cos, f α LB fcos α UB fcos α LB cos < f cos fcos α UB 1, f cos fcos α LB 0, f sus > fsus α UB fsus µ sus x) = α UB f sus, f α LB fsus α UB fsus α LB sus < f sus fsus α UB 1, f sus fsus α LB

10 Susanably 016, 8, of 0, f edc > f α UB edc f µ res x) = α UB edc f edc, f α LB f α UB edc f α LB edc < f edc f α UB edc edc 1, f edc f α LB edc where µ cos, µ sus, and µ res are sasfacon level of cos, susanably, and reslence obecves, respecvely. Sep. Conver mul-obecve model no sngle obecve Varous neracve approaches are proposed o solve mul-obecve problems. Selecon of a suable soluon mehodology for a ceran mul-obecve opmzaon problem s no easy, as has been made abundanly clear [16]. In hs sudy, he fuzzy lngusc wegh-based mehod s proposed by mprovng Werner s fuzzy and operaor mehod [17]. The proposed mehod aes advanage of boh Werner s and he fuzzy-weghed mehod. The deal of proposed mehod s gven as follows. In pracce, DMs feel comforable assgnng mporance of obecves n lngusc erms. In hs proposed mehod, he fuzzy lngusc varables are suggesed o assgn he mporance of obecves. Table 1 shows he fve-scale mporance level as rangular fuzzy number adoped from Wang and Lee [18]. Suppose ha decson-mang panel consss of n DMs, hen he mporance of obecves can be esmaed as follows. Table 1. Seven-scale fuzzy lngusc varable for mporance level. Imporance Level Abbrevaon Fuzzy Number Very Low VL 0,0,0.) Low L 0.05,0.,0.35) Medum Low ML 0.,0.35,0.5) Medum M 0.35,0.5,0.65) Medum Hgh MH 0.5,0.65,0.8) Hgh H 0.65,0.8,0.95) Very Hgh VH 0.8,1,1) 1) Se he lngusc varables for he mporance of obecves. ) Evaluae he mporance of obecves based on lngusc varables from Table 1. 3) Aggregae each of he fuzzy number usng AFN q = ω pes 1 + ω pes ωn pes n, ωmos 1 + ω mos n ωn mos where AFN q s aggregae fuzzy number of q h obecve and ωn pes percepon of mporance for q h obecve. ) Esmae he fuzzy wegh of q h obecve as shown below. ϖ q = ωpes q + ωq mos + ω op q where ωq pes, ωq mos, ωq op ) = AFN q, q = 1,, 3 number of obecves. 5) Calculae he normalzed fuzzy weghs of obecves by: ϖ q ϖ q = ϖ q q, ωop 1 + ω op ωn op ) n, ω mos n, ωn op ) s n h decson maer

11 The presened supply chan ncluded fve supplers locaed a Karach and Fasalabad ces of Pasan, Hyderabad cy of Inda, Dhaa cy of Bangladesh, and Shaoxng cy of Chna. Three poenal locaons of manufacurng facles are locaed n Karach, Pasan, Hyderabad, Inda, and Kolaa, Inda. Four cusomer zones are chosen o sell he produc locaed n Karach, Pasan, Lahore, Pasan, Mumba, Inda, and Delh, Inda. Karach, Pasan, Delh, Inda, and Hyderabad, Susanably 016, 8, of 6) Fnally, he sngle obecve model usng mproved Werner s mehod can be formed as below. ) maxmze θζ θ) ϖ 1 ζ 1 + ϖ ζ + ϖ 3 ζ 3 subec o µ cos x) ζ 0 + ζ 1 µ sus x) ζ 0 + ζ µ res x) ζ 0 + ζ 3 ζ 0, ζ 1, ζ, ζ 3 [0, 1] Sysem consrans 6 38) where, θ denoes he coeffcen of compensaon and ζ 1, ζ, and ζ 3 are he dfference beween sasfacon level of obecves wh her mnmum sasfacon level. Tha s, ζ 1 = µ cos ζ 0, ζ = µ sus ζ 0, and ζ 3 = µ res ζ 0. ϖ 1, ϖ, and ϖ 3 are he normalzed weghs for cos, susanably, and reslence obecves, respecvely. Sep 5. Deermne he soluon mehod parameers To solve he mahemacal models developed n Sep, he values of coeffcen of compensaon θ) and relave mporance of obecves ϖ q) are deermned. Sep 6. Solve he model The mahemacal models developed n Sep are solved usng requred model and soluon mehodology parameers. If decson maers are no sasfed wh he resuls, hey can provde anoher soluon by modfyng he soluon mehod parameers.e., θ and ϖ q). If decson maers wan o modfy value of α, hen hey mus resar he process a Sep.. Numercal Example In he case when real daa are no avalable, a es problem s developed based on a hypohecal supply chan, where daa are conduced based on reasonable assumpons and several publc resources. In real lfe mplemenaon, requred daa can be obaned from varous sources, such as nsallaon and producon coss can be obaned from already presen manufacurng facles. Transporaon coss beween Susanably facles 016, can 8, 1038 easly be obaned from avalable ransporaon servces. In hs example, 1 supply of 3 chan rs s esmaed by usng reslence ndex as dscussed above. To solve he proposed model, a garmen In hs example, supply supply chan schan chosen, rs s whch esmaed consss by usng of fve reslence poenal ndex supplers, as dscussed hreeabove. manufacurng To solve facles, he proposed four cusomer model, a zones, garmen hree supply collecon chan ceners, s chosen, wo whch resale consss mares, of fve wopoenal flocngsupplers, ndusres, andhree womanufacurng reclamaon mlls, facles, as shown four cusomer n Fgurezones,. Ths hree numercal collecon example ceners, assumes wo resale ha mares, he supply wo chan flocng s producng ndusres, sngle and garmen wo reclamaon produc.e., mlls, eans. as shown n Fgure. Ths numercal example assumes ha he supply chan s producng sngle garmen produc.e., eans. Suppler Manufacurng facly Collecon cener Cusomer Fber reclamaon mll Flocng ndusry Fgure.. Supply chan newor of case example.

12 Susanably 016, 8, of The presened supply chan ncluded fve supplers locaed a Karach and Fasalabad ces of Pasan, Hyderabad cy of Inda, Dhaa cy of Bangladesh, and Shaoxng cy of Chna. Three poenal locaons of manufacurng facles are locaed n Karach, Pasan, Hyderabad, Inda, and Kolaa, Inda. Four cusomer zones are chosen o sell he produc locaed n Karach, Pasan, Lahore, Pasan, Mumba, Inda, and Delh, Inda. Karach, Pasan, Delh, Inda, and Hyderabad, Inda are seleced for locaons of collecon ceners. Mal and Lbya are seleced as resale mares. Poenal locaons of flocng ndusres are locaed a Karach, Pasan and Dhaa, Bangladesh, whereas, poenal reclamaon mlls are locaed a Kolaa, Inda and Fasalabad, Pasan. The decsons ha have o be made here are followng: A number of manufacurng facles requred o open and her locaons. The amoun of producs produced a each opened facly and whch cusomer zones sasfed from each opened facly. Supplers seleced for supplyng maeral o each opened manufacurng facly. Quany of maeral o be purchased from each seleced suppler Number and locaons of collecon ceners opened. Locaon of recyclng facles.e., flocng ndusry and reclamaon mll) preferred for recyclng used producs. Locaon of resale mare and quany of producs ha can be resale o hese mares..1. Daa populaon The collecon of daa was performed o solve he model and generae useful resuls. The rangular fuzzy parameers ϑ are esmaed by nally calculang he mos lely ϑ mos value of parameers. These mos lely values of parameers were pced from varous sources such as SeaRaes [19] for ransporaon dsances and coss and CargoRouer [0] for CO emssons) some reasonable assumpons were made, and all requred calculaons were done beforehand. Thereafer, wo random numbers n 1, n ) are generaed beween 0. and 0.8 usng unform dsrbuon and he pessmsc ϑ pes and opmsc ϑ op values of fuzzy number ϑ are esmaed as follows. ϑ pes = 1 n )ϑ mos ϑ op = 1 + n 1 )ϑ mos All he requred daa he mos lely value) are presened n Appendx A wh sources.e., eher offcal daa or hypohecal daa)... Resul and Dscusson The crsp susanable and reslen model s solved usng α = 0.90 o oban payoff values. Payoff values.e., α-lb and α-ub) of hree obecves are shown n Table. Table. Payoff values α-lb and α-ub). Obecve Funcons Toal Supply Chan Cos $) Susanably KgCO ) Expeced Dsrupon Cos $) Mnmze oal supply chan cos 1,08, , ,18.30 Mnmze susanably 1,86, , , Mnmze expeced dsrupon cos 1,96, , , I can be seen from resuls ha all hree obecves,.e., economc, susanably, and reslence, of supply chan newors are conflcng n naure see Fgures 3 5). If an organzaon wans o consder he economc perspecve, Kolaa s a suable locaon for a manufacurng facly. On he

13 Cos $) Cos $) Mnmze oal supply chan cos 1,08, , ,18.30 Mnmze susanably 1,86, , , ,96, , , Mnmze expeced Susanablydsrupon 016, 8, 1038 cos 13 of I can be seen from resuls ha all hree obecves,.e., economc, susanably, and reslence, supplykarach chan newors arelocaon conflcng n susanably naure see Fgures 3 5). If and an organzaon o oherofhand, s suable from perspecve Hyderabadwans s suable consder economc perspecve,smlarly, Kolaa sbased a suable locaon for aand manufacurng facly. he locaon fromhe reslence perspecve. on procuremen ransporaon cos,on suable oher are hand, Karach s suable Dhaa, locaonand fromhyderabad. susanably perspecve and Hyderabad s a suable supplers locaed n Shaoxng, Alernavely, supplers locaed Karach locaon from reslence perspecve. Smlarly, based on procuremen and ransporaon cos, and Dhaa are suable choces when susanably obecve s gven prory over oher obecves. suable supplers are locaed n Shaoxng, Dhaa, and Hyderabad. Alernavely, supplers locaed Resuls show ha supplers wh hgher reslence ndex or lesser probably of dsrupons are gven a Karach and Dhaa are suable choces when susanably obecve s gven prory over oher prory when he reslence obecve s consdered. Smlarly, manufacurng facly and collecon obecves. Resuls show ha supplers wh hgher reslence ndex or lesser probably of ceners are open n he hghes reslence ndex locaons. The reslence obecve ensures ha he dsrupons are gven prory when he reslence obecve s consdered. Smlarly, manufacurng supply chan newor should consder dsrupon rss n advance. Ths mnmzes he rs of droppng facly and collecon ceners are open n he hghes reslence ndex locaons. The reslence supply chan performance durng a dsrupon even. The mpac of dsrupon dsruponrss rssncan be mnmzed obecve ensures ha he supply chan newor should consder advance. Ths by: 1) selecng supplers based on her adoped reslence level and he probably ofmpac dsrupon mnmzes he rs of droppng supply chan performance durng a dsrupon even. The of rssdsrupon n supplers ) esablshng manufacurng facles, collecon ceners, andlevel oher rsslocaons; can be mnmzed by: 1) selecng supplers based on her adoped reslence servce o locaons where he probably of dsrupon rss) areesablshng low or reslence ndex score andfacles he probably of dsrupon rss n supplers locaons; manufacurng of locaon s hgh; 3) ransporng mnmum quany of maeral form hgher rs zones and vce facles, collecon ceners, and oher servce facles o locaons where he probably of dsrupon rss ndex score of ha locaon s hgh; 3) ransporng mnmum quany from of versa; andare ) low s or alsoreslence found from hs sudy s no a suable choce o selec ey supplers maeral formbecause hgher rs vce versa; anddensy, ) s also found from hs sudy hahgh s no a he same regon hszones leadsand o hgher supply whch s vulnerable durng mpac suable choce o selec ey supplers from he same regon because hs leads o hgher supply and low probably HILP) rs evens. densy, whch s vulnerable durng hgh mpac and low probably HILP) rs evens. Lbya for resale Suppler Manufacurng facly Fber Susanably 016, 8, 1038 reclamaon mll Collecon cener Cusomer Flocng ndusry 1 of 3 Fgure 3. Economcal supply chan newor. Fgure 3. Economcal supply chan newor. Lbya resale mare Suppler Manufacurng facly Fber reclamaon mll Collecon cener Flocng ndusry Fgure Susanablesupply supply chan chan newor. Fgure..Susanable newor. 6 Cusomer

14 Suppler Manufacurng facly Fber reclamaon mll Cusomer Collecon cener Flocng ndusry Susanably 016, 8, of Fgure. Susanable supply chan newor. 6 Mal for Resale Suppler Manufacurng facly Fber reclamaon mll Cusomer Collecon cener Flocng ndusry Fgure5.5.Reslen Reslen supply supply chan Fgure channewor. newor. second sepof of he soluon mehodology s o develop membershp funcon. The The second sep heproposed proposed soluon mehodology s o fuzzy develop fuzzy membershp The fuzzy membershp funcons for sasfacon level of each obecve areobecve gven below. funcon. The fuzzy membershp funcons for sasfacon level of each are gven below. 0, 0, 1,86, f cos µcos x ) = 1,86, ,08,865.00, 1,1,86, f cos cos x ) f cos > 1, 86, f cos 1, 86, , 08, < f cos 1, 86, f cos 1, 08, , 1, 08, f cos 1, 86, , 08, , 86, , 0, f sus f> 307, 9.90 cos 1,08, µsus x ) = µres x ) = 307,9.90 f sus 307, ,78.30, 1, 0, 331, f edc 331, ,975.10, 1, 80, < f sus 307, 9.90 f sus 80, f edc > 331, , < f edc 331, f edc 87, The proposed model s solved usng developed Fuzzy weghed mehod and resuls are compared wh Werner s mehod see Table 3). Resuls of Werner s mehod and proposed mehod show ha he proposed mehod s more flexble as also consdered fuzzy mporance level of obecves. Table 3. Opmal resuls usng Werner and proposed Fuzzy weghed mehods. Mehod µcos µsus µres Toal Supply Chan Cos $) Susanably KgCO ) Reslence $) Werner s Mehod ,088, , , Proposed Mehod ,5, , , Noe: These opmal resuls are obaned a α = 0.9, θ = 0.5, v1 = 0.199, v = 0.11, and v3 = Sensvy Analyss The deals of he sensvy analyss of proposed soluon mehod are gven n Table. The model s solved usng he proposed fuzzy lngusc wegh mehod by varyng α and θ values. Fgures 6 8

15 Susanably 016, 8, of show he graphcal represenaons of sensvy analyss based on dfferen α values, respecvely. We assume ha DMs reach a fnal soluon a α = 0.9 and θ = hghlghed row) based on DMs preferences, whch resuls n a supply chan newor as shown n Fgure 9. The fnal supply chan requred o open a manufacurng facly n Kolaa and procure maeral from Shaoxng, Chna, and Dhaa supplers. The opmal locaon for he collecon cener s Karach where used producs can be processed. The reusable producs can be sen o Mal, Afrca for donaons. Whle he remanng used producs wll be sen o he flocng ndusry locaed a Karach and reclamaon mll locaed a Kolaa. Table. Sensvy analyss of proposed soluon mehodology. α θ µcos µsus µres Operaonal Cos $) Susanably KgCO ) Reslence $) ,588, ,, ,, , , ,7.0, , , ,530, ,197, ,197, , , , , , , ,5, ,3, ,130, ,336, , , , , , , , , , 8, 1038 Susanably Susanably 016,1.00 8, 1038 Fgure 6. Achevemen level of obecves a α = 0.0. Fgure Achevemen level level of αα = 0.0. Fgure 6.6.Achevemen ofobecves obecvesaa = 0.0. Fgure7.7.Achevemen Achevemen level level of αα = Fgure ofobecves obecvesaa = Fgure 7. Achevemen level of obecves a α = of 3 16 of 3

16 Susanably 016, 8, of Fgure 7. Achevemen level of obecves a α = Susanably 016, 8, 1038 Fgure 8. Achevemenlevel level of α =α0.90. Fgure 8. Achevemen of obecves obecvesaa = of 3 87, 88 6, , , , , , , , , , , , 1800 Reusable send o Mal Suppler Manufacurng facly Fber reclamaon mll Collecon cener Cusomer Flocng ndusry Fgure 9. Fnal Fnal Supply Supply chan chan newor based on DMs preferences wh maeral flow n wo perods. Conclusons 5. Concluson Ths sudyfocuses focuses on developng susanable and reslence supply chanbynewor by Ths sudy on developng susanable and reslence supply chan newor consderng consderng economc, green, and reslence paradgm of supply chan. The research proposed a economc, green, and reslence paradgm of supply chan. The research proposed a possblsc fuzzy possblsc fuzzy mul-obecve programmng-based handle conflcng obecves, mul-obecve programmng-based approach o handle approach conflcngoobecves, such as supply chan such as supply chan coss, carbon emssons, and reslence. The sgnfcan conrbuon of hs coss, carbon emssons, and reslence. The sgnfcan conrbuon of hs research s he ncluson research s hefacor ncluson of on a reslence based ondrven Reslence a daa drven ool n he of a reslence based Reslencefacor Index, a daa ool Index, n he desgn of he susanable desgn of he susanable supply chan newor by consderng nne maor supply chan rss. supply chan newor by consderng nne maor supply chan rss. Furhermore, a fuzzy-weghed Furhermore, a fuzzy-weghed Werner s neracve mehod based soluon mehodology s Werner s neracve mehod based soluon mehodology s proposed o solve a possblsc fuzzy proposed o solve a possblsc fuzzy mul-obecve model. Thus, hemehodology mahemacalcan model and mul-obecve model. Thus, he mahemacal model and soluon provde soluon mehodology can provde a qualy soluon o decson maers. I s found from hs research a qualy soluon o decson maers. I s found from hs research ha dsrupon rss creae chaoc ha dsrupon rss creae chaoc suaons for managers and managng are a prory for suaons for managers and managng shorages are a prory for hem.shorages Durng hese dsrupon hem. Durng hese rss, sources managers o use alernae o mnmze shorages and rss, managers ry dsrupon o use alernae o ry mnmze shoragessources and losses, hs decson leads o losses, hs decson leads o declne n susanable performance due o possble ncremen n: 1) declne n susanable performance due o possble ncremen n: 1) emboded carbon fooprns; emboded carbon CO fooprns; ) ransporaon CO emsson; and 3) economc losses. ) ransporaon emsson; and 3) economc losses. As hs s he prmary wor As hs s he prmary wor of of developng developng susanable susanable and and reslen reslen supply supply chan chan newor newor desgn desgn under sochasc and recognve unceranes usng a possblsc fuzzy programmng under sochasc and recognve unceranes usng a possblsc fuzzy programmng approach, approach, many possble fuure research avenues avenues can can be be defned defned n n hs hs conex. conex. For example, hs research many possble fuure research For example, hs research ulzes he concep of expeced dsrupon cos o measure reslence n supply chan newor; wll ulzes he concep of expeced dsrupon cos o measure reslence n supply chan newor; wll be be valuable o consder oher measures such as supply chan densy and node crcaly as he obecve funcon. Furhermore, real-me GIS daa can be ulzed o calculae he probably dsrupon rss n varous regons. The model can also be exended by ncorporang dfferen ransporaon modes and o consder road resrcons, for example, heavy rucs may no ener some roads.

17 Susanably 016, 8, of valuable o consder oher measures such as supply chan densy and node crcaly as he obecve funcon. Furhermore, real-me GIS daa can be ulzed o calculae he probably dsrupon rss n varous regons. The model can also be exended by ncorporang dfferen ransporaon modes and o consder road resrcons, for example, heavy rucs may no ener some roads. Acnowledgmens: Ths research was suppored by he Basc Scence Research Program hrough he Naonal Research Foundaon of Korea NRF) funded by he Mnsry of Educaon, Scence and Technology 01R1A1A056338). Ths research was also suppored by Hanyang Unversy, Korea ). Auhor Conrbuons: Sona Irshad Mar developed he concep and mahemacal model. Muhammad Saad Memon drafed and revsed he manuscrp. Young Hae Lee supervsed he overall wor. All auhors read and approved he fnal manuscrp. Conflcs of Ineres: The auhors declare no conflc of neres. Appendx A The coss of nsallaon for a manufacurng facly and collecon ceners are esmaed as shown n Tables A1 and A, respecvely. The nsallaon coss are hypohecal daa based on reasonable assumpons. Dependng on he land value, machne nsallaon cos, and labor wages, he cos of nsallaon and producon cos dffer. Karach s consdered as he mos expensve land value whle Kolaa as mos economcal locaon. Smlarly, producon cos, maeral cos from each suppler, processng coss a fber reclamaon mlls, flocng ndusry, and collecon ceners are se as shown n Tables A3 A6. I s assumed ha mos lely prce of fnshed produc s $30. Capaces of poenal manufacurng facles are consdered hgher han oal demand of cusomer zones, whch wll help o analyze cenralzed and decenralzed newor opons. However, capaces of he poenal suppler are consdered less han oal demand o analyze mul-sourcng sraeges. Table A1. Insallaon cos of manufacurng facly $). Facly Karach Hyderabad Inda) Kolaa Manufacurng facly 900, , ,000 Table A. Insallaon cos of collecon cener $). Facly Karach Delh Hyderabad Inda) Collecon cener 300,000 00,000 50,000 Table A3. Producon cos of produc a poenal manufacurng facles $/un). Facly Karach Hyderabad Inda) Kolaa Perod Manufacurng facly Table A. Maeral cos from poenal supplers and her producon capacy $/un). Suppler Locaon Karach Fasalabad Hyderabad Inda) Dhaa Shaoxng Perod Purchase cos Table A5. Processng cos of produc a poenal recyclng ceners $/un). Facly Locaon Karach Fasalabad Kolaa Dhaa Perod Reclamaon mll _ _ Flocng ndusry

18 Susanably 016, 8, of Table A6. Processng cos of produc a poenal collecon ceners $/un). Locaon Karach New Delh Hyderabad Inda) Perod Processng cos The probably of dsrupon rss a poenal locaons of supplers, manufacurng facles, and collecon cener are esmaed usng Reslence Index RI) proposed by [1]. Reslence ndex and he normalzed probably of dsrupon rs of poenal locaons are shown n Table A7. Hgher reslence ndex score means a lesser probably of dsrupon rss and vce versa. Table A7. RI and normalzed probably of dsrupon rs of poenal locaons. Regon Pasan Inda Bangladesh Chna Poenal locaon Karach Fasalabad Hyderabad Inda) New Delh Kolaa Dhaa Shaoxng Perod Reslence Index 0 100) Relave Probably of dsrupon rss Transporaon coss beween poenal locaons of supplers, manufacurng facles, cusomer zone, collecon ceners, flocng ndusry, fber reclamaon mlls, and resale mares are shown n Tables A8 and A9 for perod 1 and perod, respecvely. Transporaon coss beween poenal locaons are esmaed based on he sngle produc Jeans Trouser). I s esmaed ha 8800 uns of produc can be loaded per TEU. The un ransporaon coss are esmaed usng Google map for he shores dsance beween locaons, also usng avalable ransporaon roues search avalable from SeaRaes [19]) and by gaherng quoaon from ransporaon companes. The ruc-waer freghs are consdered for cross-border shppng, commonly called Fshy-bac ransporaon mehod.

19 Susanably 016, 8, of Table A8. Un ransporaon cos beween poenal locaons n perod 1 $/un). Poenal Locaon Karach Fasalabad Lahore Hyderabad Inda) Kolaa New Delh Mumba Dhaa Shaoxng Mal Sabha Karach _ Fasalabad _ Lahore _ Hyderabad Inda) _ Kolaa _ New Delh _ Mumba _ Dhaa _ 0.15 Shaoxng _ Table A9. Un ransporaon cos beween poenal locaons n perod $/un). Poenal Locaon Karach Fasalabad Lahore Hyderabad Inda) Kolaa New Delh Mumba Dhaa Shaoxng Mal Sabha Karach _ Fasalabad _ Lahore _ Hyderabad Inda) _ Kolaa _ New Delh _ Mumba _ Dhaa _ Shaoxng _

20 Susanably 016, 8, of To esmae he envronmen mpac from supply chan operaons, CO emsson durng producon, recyclng, and ransporaon of produc are esmaed. I s esmaed ha a par of Jeans produces 33. g of CO durng s lfe cycle, ou of whch 0% accouns only for producon and pacagng process, 9% of raw maeral producon, and 3% n recyclng or landfll [1]. In hs case, CO emssons durng producon a dfferen locaons are se as shown n Table A10. The CO emsson per capa s used as a bass o dfferenae he oal emsson a dfferen locaons. CO emsson per capa s colleced from World Ban daa []. CO emsson durng ransporaon s esmaed from CO emsson ndex usng cargo rouer calculaor CargoRouer [0]). CO emsson ndex defned as he amoun of CO released per un of gaseous, lqud and sold fuels used [3], s esmaed n grams of CO released. Tables A11 A13 represen he emboded carbon fooprns, CO emsson durng processng a collecon ceners, and CO emsson durng he recyclng process. Table A1 shows he CO emsson durng ransporaon beween poenal locaons based on dsance raveled and mode of ransporaon used. Table A10. CO emsson durng producon gco /un). Facly Karach Hyderabad Inda) Kolaa Perod Emsson durng producon Table A11. Emboded carbon fooprns of maeral comng from suppler gco /un). Suppler Locaon Karach Fasalabad Hyderabad Inda) Dhaa Shaoxng Perod carbon fooprns Table A1. CO emsson durng processng a collecon ceners gco /un). Locaon Karach New Delh Hyderabad Inda) Perod CO emsson Table A13. CO emsson durng recyclng process gco /un). Locaon Karach Fasalabad Kolaa Dhaa Perod Reclamaon mll _ _ Flocng ndusry

21 Susanably 016, 8, of Table A1. Carbon emsson beween poenal locaons n perod 1 and perod gco /un). Poenal Locaon Karach Fasalabad Lahore Hyderabad Inda) Kolaa New Delh Mumba Dhaa Shaoxng Karach _ Fasalabad _ Lahore _ Hyderabad Inda) _ Kolaa _ New Delh _ Mumba _ Dhaa _ Shaoxng _ Fnally, he mporance of obecves based on decson maers preferences s gven n Table A15. The demand of new producs a dfferen cusomer zones and percenage of used producs recovered from hese cusomer zones are assumed as shown n Table A16. Reusable producs are assumed o be donaed o NGOs n Sabha, Lbya and Mal, Afrca mares. Table A15. Imporance of obecves based on decson maers preferences. Obecve Funcons Decson Maer Preferences Fuzzy Calculaons DM1 DM DM3 DM AFN FW NFW Cos ML L MH L 0.00,0.350,0.500) Susanably MH H MH H 0.575,0.75,0.875) Reslence H M MH H 0.538,0.688,0.838) Noe: AFN = Aggregae fuzzy number, NFN = Normalzed fuzzy number, NFW = Normalzed fuzzy wegh. Table A16. Demand of producs a cusomer zones and percenage of used producs recovered. Locaon Karach Lahore New Delh Hyderabad Inda) Perod Demands uns) Percen of recovered used producs 57% 59% 51% 5% 55% 57% 5% 53%

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