Study of Municipal Solid Wastes Transfer Stations Locations Based on Reverse Logistics Network

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1 9 Sudy of Municial Solid Wases Transfer Saions Locaions Based on Reverse Logisics Newor Liling Yin *, Jianqin Zhou School of Economics and Managemen Beijing Jiaoong Universiy * bornowin076@6.com Absrac: Locaion of he refuse ransfer saions need o consider he cos-effeciveness for minimizing he cos and minimal imac on he surrounding residens in social benefis. This aer builds a muli-objecive mahemaical model, hrough using he logisics sysem locaion heory. For ease of calculaion, give he corresonding weighs o he economic and social benefis, and mae i ino a single objecive funcion. Solve i wih he corresonding examle. Finally, deermine he reasonable lace for he refuse ransfer saions. Keywords: Municial Solid Wases (MSW); Reverse Logisics Newor; Refuse Transfer Saion; Locaion; I. Inroducion Municial Solid Wases (MSW) refers o he divisions wihin he urban eole in daily life and aciviies of he solid refuse, including households, ublic laces and sree sweeing refuse, hosial refuse, business life refuse. Wih he raid urbanizaion and economic develomen, municial solid wases roblem has become increasingly rominen. Refuse is growing a average rae of 8. ercen currenly in he world annually; while China's growh rae is over 0%.China has become one of he mos serious counries in which he ciies are surrounded by he refuse in he world. A resen he cumulaive soc ile of municial solid wases have accumulaed over 70 billion ons, covering abou 80 million mu in recen years, and a an average annual rae of.8% growh. Abou 688 ciies naionwide, in addiion o he couny sea, here are exising / of he medium-sized ciies surrounded by refuse, and here is / of he ciy has no suiable laces for refuse iling u []. The communiy consumes a large amoun of manower and maerial resources for refuse removal, ransoraion and disosal every year, in aricular he issue of refuse ransfer. The difficuly of refuse ransfer caused a number of local consrucion auhoriies aenions. Refuse ransfer saion is he life of he masses need o be buil. If buil in a lace far away from residenial areas, refuse collecion would become inconvenien, and would lose he meaning of ransfer. Everyone wans o hrow refuse, bu all would no wan o build a refuse ransfer saion near heir houses. So where he refuse ransfer saions should be buil becomes a roblem. The refuse collecion, ransoraion, ransfer and a series of relaed rocesses are he rimary lin of municial solid wase managemen sysem. I is a rocess ha he refuse from scaered o he cenralized, which belongs o he scoe of reverse logisics. From he social oin of view, refuse rocessing and recycling are a ey comonen of susainable develomen. The refuse ransfer saion searaes he collecion and disosal of municial solid wases. Therefore, locaion of he refuse ransfer saion becomes a crucial elemen of municial solid wase reverse logisics newor oimizaion. This aer build a mahemaical model hrough using he logisics faciliies locaion heory, and solve i hrough he relevan algorihms o deermine he oimal locaion of refuse ransfer saions, in order o mae he cos resen value of he municial solid wases sysem o be minimum, while also achieving he goal o minimize he imac on he surrounding residens, which called he social benefis. This is criical o he domesic refuse recycling reverse logisics newor oimizaion. II. Reviews The municial solid wases reverse logisics sysem mainly includes collecion oins, ransfer saions and disosal sies. These hree ars, as well as comlicaed ransor roues beween hem form he whole of municial solid wases reverse logisics newor srucure. In he reverse logisics newor, he refuse ransfer saion connecs collecion oins wih disosal sies, as a bridge among hem. I lays an imoran role in he logisics sysem. In recen years, municial solid wases reverse logisics newor oimizaion roblems have aroused much aenion of domesic and abroad scholars. In he refuse ransfer saion locaion oimizaion, Hu Shuanghai and He Bo (007) [] analysed he facors which should be considered during he esablishmen of refuse ransfer saions, and se a locaion evaluaion index sysem. Based on heir research ino he field, Wang Jinhua, Sun Kewei and Fang Zhen(008) [] develoed he heory of sie selecion of municial refuse ransfer saions and named such basic necessary communiy faciliies as non-execed faciliies, for heir environmen effec on eole s daily life. They oined ou ha locaion bicrieria in he non-execed-ye faciliy are minimum and maximum crierion. However, he aer did no esablish he aroriae model based on he acual siuaion o verificae. He Bo, Yang Chao and Zhang Hua(007) [] sudied he design and oimizaion roblems of refuse recycling muli-layer of reverse logisics newor, including he locaion selecion of ransfer saions and disosal sies, a he same ime esablished of muli-arge ure Ineger Programming model The h Inernaional Conference on Oeraions and Suly Chain Managemen, Hongong & Guangzhou, Jul. o Jul., 00

2 9 o mee he wishes of he ublic. Designed a wo-hase decomosiion algorihm based on heurisic o consruc a refuse recycling muli-layer reverse logisics newor. However, he aer did no mae a discoun for he model. Jia Chuanxing, Peng Xuya and Liu Guoao(006) [] esablished a model o mae he resen value of he sysem oal cos o be minimum hrough using he Ineger Programming mehod afer deermining he refuse ransfer saion o be he choice of sie, and achieved he overall oimizaion. A he same ime hey eleced he oimal combinaion of ransfer saions from he choice of sies, and deermined he amoun of refuse ransfer saions acceed of hem. Bu he aricle made he resen value of he whole sysem o be minimized wih view of he economic ersecive. The exising lieraures consider he building reverse logisics newor roblem basically from he economic ersecive, and always build single-objecive. Mixed Ineger Programming model, objecive funcion of which generally is o minimize he oal cos of building logisics newor sysem. Bu he refuse ransfer saions are really a ind of ublic faciliies. This means ha in locaion no only he cos-effeciveness should be considered, bu also he social benefis. This ind of locaion roblems becomes a muli-objecive oimizaion roblem. III. Building he Municial Solid Wases Transfer Saion Locaion Model Descriion of he roblem Municial solid wases reverse logisics newor should be he highes level of general acceance by he ublic, which means he smalles imac on he environmenal and he lowes cos. This aer uses he cos of ransfer saions consrucion, oeraion fee and ransoraion cos o reflec he cos-effeciveness. The urose is ha minimize he economic cos. As he refuse ransfer saion has unredicable effecs on he surrounding environmen, i should be away from residenial areas as far as ossible o mae he social benefis under consideraion. The wo objecives, Economic and social benefis, are inerlined and influence each oher, which form a arge sysem. Therefore municial solid wases ransfer saion locaion is a muli-objecive rogramming roblem. I mus be co-ordinae he lanning and reasonable arrangemen, in order o achieve he bes resuls. This is he ulimae goal of he model building. Afer se he relaed evaluaion index sysem, we use he analyic hierarchy rocess o evaluae comrehensively and ge he ransfer saions alernaive addresses. Using Ineger Programming mehod o esablish a model, in which he oal resen value cos of refuse reverse logisics sysem is minimum while social benefi is maximized. Then oimal oins of refuse ransfer saion are seleced ou from alernaive addresses o achieve he overall oimizaion. Model Assumions () The number of refuse collecion oins has been idenified. Each collecion oin is locaed near residenial areas, while refuse disosal sies are buil by he governmen in he designaed locaions. () The caaciy of each refuse collecion oin and ransfer saion is a cerain size. ()The refuse in he collecion oin can only be ransored direcly o he ransfer saion, and hen ransored o he disosal sie from he ransfer saion, and can no be direcly ransored o he disosal sies. The refuse in he collecion oins can only be ransored o a neares refuse ransfer saion, bu a refuse ransfer saion can acce refuse from many collecion oins. The refuse in he ransfer saion can be shied o more han one disosal sies, and disosal sies can acce refuses from a number of refuse ransfer saions. ()The refuse shiing cos of uni disance is nown as a consan. ()The ransoraion cos of domesic refuse has simle linear relaion wih is ransoraion disance. In his case, in he rocess of he enire refuse reveres logisics, he cos from he economic ersecive deends largely on ransor coss of refuse from collecion oins o he ransfer saion and from he ransfer saion o he disosal sie, he ransfer saion fixed invesmen coss and he ransfer saion oeraing coss during he using eriod. The hree inds of coss above-menioned are inerlined and muual consrain wih each oher. All of hem are closely relaed o he locaion and he size of he ransfer saions. Definiion of Parameers and Decision Variables Definiion in he Model ()i I he subscris of collecion oins; K subscris of ransfer saions; j J subscris of disosal sies; () T means he lifesan of he ransfer saions; () r reresens resen value discoun rae; ()A is oeraing coss of he ransfer saion(yuan er Ton), including dereciaion charges and mainenance fees of equimen and faciliies, saff coss of ransfer saion oeraions, uiliies suoring maerials fee and oeraing cos of he ransor rucs; () B i means he ransoraion coss involved in ransoring one on refuse for one ilomeer over he delivery roue from he refuse collecion oin "i" o he ransfer saion "",(yuan - m - ). (6)C j means he ransoraion coss involved in ransoring one on refuse for one ilomeer over he delivery roue from he ransfer saion "" o he disosal sie "j", (yuan - m - ). (7)X i is he uni amoun of refuse ransored from collecion oin "i" o refuse ransfer saion "" er day ( d - ); (8)Y j is he uni amoun of refuse ransored from refuse ransfer saion "" o disosal sie "j" er day ( d - ); (9) L i is he ransor disance beween collecion oin "i" and refuse ransfer saion "" (m); The h Inernaional Conference on Oeraions and Suly Chain Managemen, Hongong & Guangzhou, Jul. o Jul., 00

3 9 (0) S j is he ransor disance beween refuse ransfer saion "" and disosal sie "j" (m); () F is he fixed invesmen of ransfer saion "" o be consruced during he lanning eriod (yuan); () Q is he caaciy size of refuse ransfer saion ""; () q i is he refuse caaciy of collecion oin "i"; () M is a large number Mahemaical model Based on he above analysis, mahemaical models can be buil as follows: Objecive funcion: m T L B i i min R = (6 X ) U i i i= = = ( + r) m T S C j j + (6 Y ) V j i= = = ( + r) 6 Y A + + ( + r) m Q W min P = q i () Subjec o: i= = L m X U = Y V i i j j i= j= X = = j= = = m i= n i Y U i i q j = i Q U M W n T j F W W = = j= = X i = n i j () () () () (6) (7) Exression () is model ha he minimum of he resen value during he lifesan, including he coss of ransfer saion consrucion, oeraion, and ransoraion refuse among he collecion oins, ransfer saions and disosal sies in he reverse logisics newor. Discoun hem hrough he discouning aroach, calculae 6d for one year. Exression () indicaes ha he negaive effec arising from ransfer saion esablishing is roorional o is scale, inversely roorional o he disance from he residenial area. Consrain equaion () ha is he amoun of refuse balance beween ransfer saions in and ou. Consrain equaion () ha is he amoun of refuse shied ou of collecion oin "i" should be less han is caaciy; Consrain equaion () ha he amoun of refuse shied ou of ransfer saion "" should be less han is size; Consrain equaion (6) ha he refuse in a collecion oin is only shied o one ransfer saion; Consrain equaion (7) means ensure ha only when he ransfer saion is buil, i can receive refuse from collecion oins; Consrain equaion (8)reresen he resricions on he size of he ransfer saions; Consrain equaion (9) ensure ha he amoun of refuse on he ransor is non-negaive. Consrain equaion (0) is he decision variable wheher o esablish a refuse ransfer saion; Consrain equaion () is he decision-maing variable ha wheher he refuse is ransored from some one collecion oin o cerain ransfer saion. Consrain equaion () is a decision variables ha wheher refuse from one ransfer saion is ransored o some one disosal sie. For ease of oeraion, we can u he muli-objecive rogramming roblem ino a single objecive. On he economic and social benefis are given a cerain weigh W and W. W and W can generally be organized by exers discussion, W ha is he weigh of cos-effecive share. The general value of i is , and i is defined as 0.6 in he ex. The objecive funcion becomes min F=0.6minR+0.minP. IV. Numerical Examles Analysis This aer use he case which in He Bo,Yang Chao and Yang X U Q (8) i i Jun s aer ha "A Muli-objecive Oimizaion Model of Reverse Logisics for Solid Refuses". There are 0 ransfer, Y 0 (9) i j saions o be chosen, and heir locaions s and, m; consrucion coss are given in Table. Disosal sie locaions s are shown in Table. Values of each =, ; j =, n arameer are shown in Table. Table gives he locaions build he wase s and oulaion of 0 collecion oins. This aer assumes ha one erson would roduce. Kg refuse er W= ransfer saion day. 0 oherwise (0) wase in he i collecion oin ransor Ui= () o he ransfer saion 0 no wase in he ransfer saion ransor o he j Vj= () disosal sie 0 no The h Inernaional Conference on Oeraions and Suly Chain Managemen, Hongong & Guangzhou, Jul. o Jul., 00

4 9 Table The Locaion and Cos of Alernaive Transfer Saion NO. horizonal verical cos(en housand yuan) Table Locaion of Disosal Sies No. horizonal verical Table Model Parameer Values Lifes Discoun Transfer saion Uni cos of an Oeraion cos ransoraion T A/yuan - (yuan - m - ) 8% 0 In order o faciliae he calculaion, recangle disance is used o measure he disance beween refuse collecion oins, ransfer saions and disosal sies. L = x x + y y () i i i Sj = x xj + y yj () In formulae () and (), x i, y i, x, y, x j, y j indicae he horizonal and verical s of he collecion oins, ransfer saions, disosal sies on he ma. Finally, u he above-menioned values ino he model of he objecive funcion. Comile algorihm rograms for Oimizaion hrough using MATLAB. The beneficial economic and social effecs will be maximized by building No., No.6, No.7 and No.9 ransfer saions, as he research resul suggess. Using MATLAB can easily do his, and his resul is more accurae han ha aer. Table No Locaion and Poulaion of he Collecion Poins Horizonal Ⅴ.Conclusion verical Poulaion(Ten housand) This aer sudies he municial solid wases ransfer saion locaion issues in reverse logisics newor. From he managemen oin of view, he consrucion and oeraion cos are requesed o be he minimum. However, from he ublic oin of view, require ransfer saion away from he living area as far as ossible, so esablish a bi-objecive ineger rogramming model. By solving he model, we can decide a reasonable locaion of he refuse ransfer saions. Furher sudies include: () The municial solid wases may deosi a he ransfer saion, so ha his become a roblem wih invenory of he locaion. () For he amoun of collecion oins is uncerain, ha is, random variables or fuzzy variables siuaion. sochasic rogramming and fuzzy rogramming model can be used o build a reverse logisics newor sysem. ()Because of he requiremens of oeraional economies of scale in he real environmen, he ime of refuse collecion and ransoraion needs o be aen ino accoun. Therefore, he roblem can be urned ino a model wih ime windows The h Inernaional Conference on Oeraions and Suly Chain Managemen, Hongong & Guangzhou, Jul. o Jul., 00

5 96 consrains, i will be more in line wih he acual siuaion. Time window consrains can be divided ino wo caegories, hard and sof ime windows consrains. The so-called hard ime window consrain is ha he service mus be carried ou in a given eriod of ime. And he sof ime windows consrain is ha he ransfer saion can rovide services in he secified eriod. However, during his ime rovided services, i mus comensae for he resuling loss. This roblem can be addressed hrough he inroducion of enaly facor. Reference [] Yan Shengjun (009). Analysis on he Causes of Municial Solid Wase and Thining of Fuure Trends, Scienific Pracice. [] Hu Shuanghai and He Bo (007).Analysis on Facor s of Solid Wases Transfer Faciliy and Treamen Faciliy Locaions, Analysis and Decision, [] Wang Jinhua, Sun Kewei and Fang Zhen (008).Research on Selecing Locaion of Municial wase Transfer Saion, Environmenal Science and Managemen, Vol., No.,7-9. [] He Bo, Yang Chao and Yang Hua (007). Oimal Design of he Muli Echelon Reverse Logisics Newor for Solid Wases Chinese Journal of Managemen Science,Vol., No., [] Jia Chuanxing, Peng Xuya, Liu Guoao (006). Esablishmen of oimizaion model for locaion of municial solid wase ransfer saion and is alicaion[j]. Aca Scieniae Circumsaniae, 6 (),97-9. Bacground of Auhors Yin Liling (987-), female, School of Economics and Managemen, Beijing Jiaoong Universiy, Maser. Zhou Jianqin (97-),male, School of Economics and Managemen, Beijing Jiaoong Universiy, Associae Professor. The h Inernaional Conference on Oeraions and Suly Chain Managemen, Hongong & Guangzhou, Jul. o Jul., 00