A HIERARCHICAL AND GEOREFERENCED APPROACH FOR FREIGHT TERMINAL LOCATION

Transcription

1 A HIERARCHICAL AND GEOREFERENCED APPROACH FOR FREIGHT TERMINAL LOCATION by Yako YAMASHITA **, André DANTAS ***, Eizo HIDESHIMA **** and Koshi YAMAMOTO ***** Introduction: In transportation, dcision-making phas has an ssntial rol in th planning contxt. Th actions of plannrs hav to b fficint and dynamic to gnrat th bst managmnt of th rsourcs and consquntly maximiz bnfits. Rcntly, th intrvning factors bcam mor complx and rlatd to political, conomical and social intrsts, which hav to b considrd in th final dcision. Howvr, transportation dcisions hav bn takn undr a limitd scop as consqunc of th application of mthodologis and modls ). According to Forts and Paiva 2), mthodologis hav bn limitd to valuat just travl tim and oprational costs in a transportation systm, which limits and crats incomplt analysis basd on cost - bnfit valuations. In this sns, as indicatd by Hhak and Strombrg 3), a nw nvironmnt with diffrnt conditions has mad plannrs raliz that nw mthods xploring computr s capabilitis to simulat complx procss ar ndd. Computational instrumnts such as th Gographical Information Systms (GIS) can contribut to ovrcom th limitations obsrvd in dcision-making activitis. GIS provids a larg varity of tools that allow plannrs to simulat multipl scnarios and to visualiz data / rsults du to its capabilitis to procss simultanously attributs and location data rlatd to gographical rality that can b combind with spcial functions for spatial analysis 4) 5). Many applications of GIS in transportation studis ar noticd in rcnt yars xploring mostly th capacity of storag and visualization associatd with modlling tchniqus. Though such applications hav gnratd svral bnfits to its usrs, thy did not xplor compltly GIS potntial in th sns that traditional transportation modls wr not concivd to fully incorporat gographical-spatial data and spatial analysis. Additionally and mayb th most important is th fact that transportation modls and GIS ar not dsignd to mak planning dcisions, although thy provid bttr accss and manipulation of th data 6). In ordr to combin th information gnratd by instrumnts such as GIS and thn rach an xtnsiv considration of th factors influncing th dcision-making, som fforts towards th dvlopmnt of Dcision Support Systms (DSS) ar obsrvd 7) 8). In ths works, it is clarly obsrvd th intntion to focus on th valuation of variabls that ar not usually considrd in transportation analysis through th manipulation of gographical and spatial lmnts using th framwork of dcision tchniqus. Both studis avoid an opration rsarch modlling, which may b implmntd without addrssing human valus and purposful human activity 9), concntrating on th managmnt of gographical-spatial information in ordr to facilitat group-dcision. Following th sam dirction of ths fforts, in this papr, w prsnt th dvlopmnt and application of th intgration of a dcision-making tchniqu (Analytic Hirarchy Procss), GIS and Rmot Snsing (RS) intnding to stablish a nw approach for th dtrmination of a fright trminal location. This nw approach is ncssary sinc traditional location thory is basd on a particular hypothsis with a small numbr of location factors usually rlatd to transport and labour costs 0), and logistic modls just focus on th minimization of distancs (costs) in th displacmnts ). In opposition to ths concptions, w propos a hirarchical and gorfrncd approach making possibl a widr considration of nw variabls and th participation of thos involvd in th dcision. In this contxt, hirarchical stands for th lvls of th dcision structur using th Analytic Hirarchy Procss (AHP), which corrsponds to on s undrstanding of th situation (goals, critria, subcritria and altrnativs) 2), and gorfrncd is rlatd to th us of information with a rfrnc in a gographical spac, rspctivly. This papr is dividd in four sctions. Aftr this introduction (sction on), th basic concpts of th AHP-GIS-RS intgration ar prsntd in th sction two in ordr to spcify th charactristics of ach lmnt as wll as thir rol in a dcision-making contxt. Nxt, w rport a cas study for th application of th AHP-GIS-RS intgration for th location of a fright trminal in Brazil, which is part of a postal transportation systm. Finally in sction four, it is discussd th rlvanc of this intgration for transportation studis as wll as som final considrations ar prsntd. 2 AHP-GIS-RS intgration for dcision-making: In th dcision contxt, plannrs ar rsponsibl to dfin th variabls involvd in a problm and to structur and analyz. Dar apud Dnsham 3) pointd out that on of th main difficultis is rlatd to th dfinition of ths variabls, sinc it is a hard task to captur and rprsnt important spatial dimnsions. Such fact may lad to th slction of incorrct variabls and consquntly dficint dcision framworks and unsatisfactory solutions may b rachd. Hnc, th participation of th dcision-makrs bcoms an ssntial issu, sinc thir slction will b th basis for th rst of th procss. Nvrthlss, th Kywords: dcision-making, trminal location, GIS, Rmot Snsing, AHP **Mmbr of JSCE, PhD, Dpt. of Civil Eng., Unvrsity of Brasilia (Campus Univrsitario Dary Ribiro, Brasilia, Brazil, TEL , FAX , -mail: yako@unb.br) ***Studnt Mmbr of JSCE, MSc, Dpt. of Civil Eng., Nagoya Institut of Tchnology (Nagoya Institut of Tch., Gokiso-cho, Showa-ku, Nagoya, Japan, TEL.FAX , -mail: andr@kik.ac.nitch.ac.jp) ****Mmbr of JSCE, Dr. Eng., Dpt. of Civil Eng., Nagoya institut of Tchnology (Nagoya Institut of Tch., Gokiso-cho, Showa-ku, Nagoya, Japan, TEL.FAX , hidshima@ac.nitch.ac.jp) *****Mmbr of JSCE, Dr. Eng., Dpt. of Civil Eng., Nagoya institut of Tchnology (Nagoya Institut of Tch., Gokiso-cho, Showa-ku, Nagoya, Japan, TEL.FAX , yama@doboku2.ac.nitch.ac.jp) 36

2 knowldg of th dcision-group is influncd by th lvl of information that is providd bfor and during th analysis. This knowldg bcoms a critical issu in transportation studis, which mostly dals with information rlatd to th gographicalspatial rality 4). In this sns, AHP-GIS-RS intgration gnrats an instrumnt capabl to provid information and computational tools undr a dcision framwork. Dvlopd by Satty 5), AHP is basd on human bing bhavior to dcid through th comparison btwn objcts until raching a dcision. Th comparison is rlatd to th assignmnt of wights according to th rlativ importanc whn comparing to pr-stablishd judgmnt critria. Using a quantitativ scal all th objcts ar compard lading to a prioritization and consqunt dcision. AHP has a simpl structur that dirctly dpnds on th knowldg of th dcision-group, which is rachd through th obtainmnt of information about th problm. Additionally, GIS capabilitis contribut to provid additional information according to th nds or doubts of th dcision-group. Th us of RS data (arial photographs and satllit imags) rducs significantly labor-work tim for thos activitis rlatd to th collction of data through survys in loco gnrating primary data and tchniqus to procss spatial modling. Hnc, information / data rlatd to th spatial location, such as land us pattrns, trrain conditions, transportation systm, distancs and aras can b obtaind and manipulatd without grat amount of invstmnt in data collction 6). This intgration can b dividd in four phass as shown in Figur. Nxt, ths phass ar dscribd in dtail: GIS & RS First Phas Scond Phas Third Phas Fourth Phas AHP Figur : Intgration of AHP, GIS and RS First Phas (Dfinition of hirarchical structur): concrning on th problm dfinition, critria idntification and altrnativ slction for valuation. AHP stablishs thortical fundamntals, whil GIS and RS provid data to diagnos th problm; Scond Phas (Judgmnts of th critria): ach of th critria is compard to th othrs. Dcision-group judgs according to th fundamntal scal dfind by Satty 5), as shown in Tabl, considring data visualizd in GIS databas; Tabl : Fundamntal Scal for Judgmnts Intnsity of importanc Dfinition Sam importanc 3 Small importanc 5 Grat importanc 7 Vry Grat importanc 9 Absolut importanc 2, 4, 6, 8 Intrmdiary valus btwn adjacnt ons /x Invrs comparison, -,9 Comparisons btwn two nxt lmnts Sourc: Saaty 5) Third Phas (rnativ prioritization): th prioritis of ach altrnativ, prviously idntifid in th First Phas of this intgration, ar calculatd. Thn, b a st of f altrnativs, whr f=, 2, n, w hav that ach f is rlatd to a priority P(f) within a rang of 0 to and obtaind through quation. q P( f ) = ψ () w= f w whr f is th altrnativ numbr and ψ f w is th priority of th last lvl of critria w in th AHP hirarchy that is obtaind through quation 2 as following: f w nl ψ = Φ (2) s= w s whr Φ w s is th rlativ priority of th critria w in th lvl s (s {, 2,., nl}) of th AHP hirarchy; Fourth Phas (Priority Analysis and altrnativ slction): using thmatic maps th dcision-group can rach th bst dcision by analyzing and comparing th diffrnt influncs of ach critria. Within this intgration, th intraction btwn GIS and th dcision-group is on of th most significant aspcts. This intraction occurs in 8 stps as shown in Figur 2. Firstly, th dcision group accsss GIS in ordr to obtain 362

3 information to b usd in th dfinition of th hirarchical dcision structur (stp ). Nxt, in stp 2, th judgmnts ar conductd, but if th dcision-group nds additional information thn go-spatial quris can b usd as rprsntd in stp 3. This stp can b rpatd as much as ndd and complmntary data can b rtrivd in ordr to liminat doubts. In th squnc, th prioritis ar calculatd in stp 4 and thn thy ar transfrrd to GIS databas (stp 5). Thmatic maps ar cratd in stp 6 basd on th final prioritis. In stp 7, th dcision-group discusss th thmatic maps in ordr to vrify vntual problms or inconsistncis. At this point, th dcision-group can ithr rach th final dcision (stp 8) or rstart th procss (stp ) or mak th improvmnt of th judgmnts (stp 2 and 3). Along th intraction, it can b noticd that according to th data rquirmnts from th dcision-group th whol procss can b adjustd and this may lad to a bttr dcision at th nd. GIS Dcision -Group Hirarchical Dcision Structur problm C C2 Cn a a2 a3. an GIS databas 2 3 Judgmnts α 2 α n α α n α α rnativ Prioritization q P( f ) = ψ w= f w 7 Analysis 8 Thmatic maps Figur 2: Stps for th intraction btwn GIS and th dcision group Dcision It is important to clarify that th application of this intgration dpnds on prvious organization and construction of a GIS databas. Such a databas can b ithr a part of a whol projct that uss th data for multipl purposs or spcifically dvlopd to solv on problm. It is clar that th construction of a spcific databas will lad to th obtainmnt of data and consquntly gnrating wasting tim and financial rsourcs. W will not b ddicatd to th discussion of this mattr but on has to b concrnd that spcific problms do nd spcial data. For instanc, th charactristics of th RS data (scal, rsolution, covr ara, tc.) dpnd on th objctivs of th dcision procss, i.., whn analyzing rgional or local problms th dfinition of suitabl data has to b adquatly idntifid. 3 Cas Study: In this sction, th AHP-GIS-RS intgration is applid in solving a ral problm rlatd to th slction of a trminal location. W us as an xampl th location dtrmination of a postal fright trminal in an urban ara as part of th Brazilian Postal and Tlgraphic Entrpris (ECT). This dcision is fundamntal in ECT oprations sinc it affcts th structur of production and as consqunc th cost of th postal srvic. In th fright oprations of ECT, many typs of trminals ar usd but w concntrat on th analysis in a spcific typ calld Dwlling Distribution Cntr (DDC). This trminal is a small trminal usd in th transshipmnt of postal fright (lttrs, small parcls, tlgrams, tc) whn a larg amount of consolidatd fright coms from biggr trminals. For instanc, in a mtropolitan ara firstly th postal fright originatd from othr citis is gathr togthr in main trminals (Opration Cntr OC and Slction Cntr - SC), whr thy suffr an initial tratmnt. In th squnc, th postal fright is movd to DDC whr it is again organizd according to th typ of th fright (urgnt, spcial or common) and th dstination insid th DDC ara. Finally, for ach district (zon of collction/distribution on foot) and circuit (rout of collction/distribution by motorbiks and small trucks or vans), rspctivly, postmn and drivrs of vhicls procss th dlivry. In som cass, du to long distancs, postmn us public transportation systm (bus, subway, train, tc), which allows a fastr and conomical displacmnt to rach th district. Aftr th compltion of th distribution, th collction activitis start in ordr to continu th whol procss of postal fright transportation. So, postmn collct lttrs from th mailboxs and vhicls ar ddicatd to transport biggr parcls from th post offics to th DDC. This fright is assmbld at DDC and thn transfrrd to th main 363

4 trminal of th mtropolitan ara. This collction/distribution (C/D) procss is prsntd in Figurs 3 and 4. It is important to mak clar that DDCs hav a totally diffrnt rol of post offics, which ar ddicatd just to rciv all typs of postal fright and srvics. This sparation is usually ncssary sinc post offics ar locatd in aras of xtrm concntration of urban activitis in opposition to DDCs that can b locatd according to logistical dfinitions. Fright from / to othr citis Customr Customr Spcial Customrs Spcial Customrs Mailboxs Post Offics OC SC DDC DDC Customr Customr Spcial Customrs Spcial Customrs Figur 3: ECT`s fright activitis Strts DDC B Bus Stop B Rsidntial ara Dirction of th C/D Walking B Bus lin (a) Figur 4: Collction and Distribution activitis a) postman b) vhicl Sinc DDC provids th ncssary facilitis to intgrat diffrnt transportation mods, cost rduction can b obtaind through optimal us of rsourcs (staff, gasolin, matrial, tc) and movmnts of C/D activitis. In this contxt, DDC location is on of th variabls to obtain such optimal cost. If fright dmand and / or othr xtrnal condition suffrs variation along th tim, th DDC rlatd rsourcs (vhicl and gnral quipmnt, prsonnl and physical spac) hav to b rorganizd in ordr to rach bttr srvics and costs, as wll th trminal location 7). DDC location is affctd by rntal and dlivry (postmn and vhicl) costs, which ar dpndnt on dmands and transportation infrastructur (strts, roads, walkways, tc). According to rports of th company 8), in rcnt yars many variations hav bn obsrvd in th oprational conditions, which its tchnical staff should valuat in ordr to vrify, for instanc, th DDC location. Howvr, it can b asily vrifid that thr is not an instrumnt to procss such an valuation considring th most important factors affcting th location of th trminal. Th mthodology currntly usd by ECT just analyzs th dmands in th srvic ara without using any mathmatical modl and this analysis is conductd in long-trm priods du to th limitations of rsourcs in th tchnical sction 9). This lads to th ncssity to apply not only th corrct and frqunt valuation but it is also ssntial to xplor th limitd rsourcs without th cration of additional costs. It would b quit natural to apply location modls as dscribd by Novas ), but that would not b appropriat. Firstly, ths modls do not considr important factors such as dmand, th conditions of th traffic systm and go-spatial rstrictions. Morovr, if it was dcidd to simulat th ntwork of ECT rlatd to DDC oprations, th basic formulation of traditional modls is not suitabl. Traditional modls ar dvotd to solv th location problm through th minimization of distancs (costs) in th displacmnts from th trminal to points of attndanc, which is not th cas Rgarding that ECT nds an instrumnt to procss dcisions in a stratgic lvl of planning, w propos th application of AHP-GIS-RS intgration to idntify potntial aras to implmnt DDC in Sobradinho City, Fdral District, Brazil. In this city, which is locatd 24 Km from Brasilia and has a population of habitants occupying an ara of 569,37 Km 2 20), ECT s oprations covr 5 districts, post offic and 2 circuits. Th currnt location of DDC is in th commrcial ara insid th district as shown in th Figur 5. A dcision group was dfind with 7 tchnicians to whom w dscribd (b) Small truck Motorbiks 364

5 our proposal and th intgration as an instrumnt to hlp in th dcision-making. As it was not our purpos to compar with othr formulations (location modls and mthodologis), w did not discuss AHP nithr th intgration by itslf. To conduct th application without additional costs, a prvious GIS databas was usd. Th digital bas (coordinat systm UTM) containing th transportation systm, dification and topography iso-lins and a group of six arial photographs was also usd composs this databas. Th Dvlopmnt Company of th Fdral District (CODEPLAN) providd both sourcs of data without costs. Additionally, th main charactristics (districts dlimitation, location of mailboxs, circuits dfinition, public transportation by bus, traffic systm) of th srvic ara in Sobradinho City wr digitalizd. GIS databas and oprations wr supportd by MSQL and MGE softwar using a PC-Workstation 300 MHz. Firstly th intrprtation of th arial photographs was conductd in ordr to slct th potntial altrnativs. Following th principls dscribd by Avry and Brlin 2), fiv catgoris of land us pattrns wr idntifid (Rsidntial Simpl and Multipl, Commrcial, Spcial and Srvic aras). In th squnc, w concntratd on th analysis of Commrcial aras sinc DDC can b only implmnt in such aras. Thus, w vrifid 9 altrnativs (f=9) of Commrcial aras that wr subclassifid in 3 classs (Local commrcial ara; Spcial commrcial ara; and Mixd commrcial ara) as shown in Figur 6. To obtain ths altrnativs, th proximity to strts / avnus, th charactristics of land us pattrns and spatial distribution (distanc) wr gard. Figur 5: ECT in Sobradinho city Mail box Spcial dlivry DDC District Strts Commrcial Commrcial 2 Commrcial 3 A rnativ Figur 6: Potntial altrnativs in commrcial aras Nxt, th dcision hirarchy was dfind. Mainly considring th basic concpts of th currnt mthodology of ECT and 365

6 th information rtrivd from GIS databas, th dcision structur in Figur 7 was rachd. Th rol of GIS databas was rmarkabl, sinc th dcision-group has nvr xprincd such intraction for dcision mattrs and many tims thy xprssd th positiv influnc in thir activitis. For instanc, whn discussing spcific critria such as fright dmand, th mosaic of arial photographs visualizd in GIS brought dcisiv information into thir valuations. Th slctd critria ar dscribd blow: Land Us intnds to quantify th fright dmand around th potntial altrnativ; Topography valuats th conditions of movmnts in fright oprations (postman and vhicls displacmnts) sinc th slop variation contributs to gnrat additional nrgy rquirmnts; Distancs quantifis th displacmnts from th potntial altrnativ to th districts of Collction / Distribution activitis; Transportation Systm considrs th xistnc of th systm, in spcial it is valuatd th bus routs and traffic systm; and Rntal cost as th DDC is always rntd such cost has to b carfully analyzd. In this hirarchical dcision structur, it can b obsrvd that th critria rachd only on lvl of sub-critria. This is du to th considration by th dcision-group that additional lvls would not significantly contribut to th final dcision. For instanc, th transportation systm critria is dividd in two sub-critria, but bus sub-critria could b analyzd according to th typs of bus routs. In th sam dirction, w could judg th traffic systm dpnding on th functionality of ach sgmnt of th ntwork. Howvr, th dcision-group optd to stablish a simpl structur, that is still an hirarchical structur not dpnding on its complx subdivisions as w can obsrv in Satty 5). Obviously, for diffrnt applications mor dtaild dcision structurs may b ncssary, but fortunatly this was not th cas. In th squnc, w mdiatd th discussion and th judgmnts of all th critria. During th judgmnt, it was ncssary to obtain mor information about th srvic ara, spcially thos rlatd to th topography critria. In this sns, w usd th Digital Trrain Modl (DTM) and a slop map of th city cratd by a trrain analysis modul of th GIS softwar. Morovr, th dcision group askd for th xact distancs from potntial altrnativs to th districts, which was obtaind from a ntwork analysis. In th judgmnt of th Land Us critria, w applid th mthodology dvlopd by Taco t al. 22) in ordr to valuat th fright dmand. This mthodology stablishs that according to th occupid ara of land us pattrns th dmand can b dfind. Finally, rntal costs for ach altrnativ wr also obtaind through rntal agncis of Sobradinho City. For ach critria, w constructd thmatic maps that wr adjustd until th dcision-group rachd th common sns. Applying th quations 2, th final prioritis P(f) wr rachd as shown in Figur 7 and Tabl 2. Considring th rsults xprssd in Figur 8, som analysis can b conductd on th final prioritis and th judgmnt procss. Analyzing th numrical valus for ach critria it can b vrifid that Topography was th gratst valu (39.09%) showing its importanc in th dcision-making. On th othr hand, th altrnativs 4, 5 and 6 ar thos with highst priority du to a positiv valuation for almost all critria xcpting only Extrnal distanc and Rntal cost. This bst st (4,5,6) is du to th proximity to grat fright attraction / gnration aras and to its topographical condition (on th highst rgion of th city). Morovr, it has a grat advantag bcaus of th road systm and th varity of bus lins as wll as th proximity to th city bus trminal. Th final priority map lads to th rcommndation of th potntial altrnativs 4, 5 and 6. Dspit of undrstanding of th rsults, th judgmnt procss was an ssntial part of th dcision-making. Th dcisiongroup was abl to intract and ask for additional information that was crucial to rach th final dcision. This is th cas of th Topography critria, which could not b corrctly valuatd without th DTM. L v l I L v l II L v l III Land Us Topography 5 6 Potntial Aras to implmnt a DDC 7 Intrnal 8 Distancs 9 Extrnal 0 Transportation Systm Roads 2 3 Bus 4 5 Rntal Cost Land Us Topography Distancs Transport Rntal Final.97% 39.09% 33.40% 6.04% 4.09% Priority Int. Ext. Road Bus 83.33% 6.67% 6.67% 83.33%.97%.22% 2.40% 3.82% % 2.97%.22% 3.55% 5.9% % A 3.97%.22%.55% 2.7% % L %.22%.55% 2.7% % T 5.97%.22% 2.40% 3.75% % E 6.97% 3.43% 5.87% 3.75% % R % 3.43% 5.87% 5.9% % N % 6.30% 9.52% 4.79% % A % 3.43% 7.% 2.7% % T % 6.30% 7.% 5.9% % I 7.72% 3.43% 7.% 2.7% % V 2.97% 3.43% 5.87% 2.53% % E % 3.43% 5.87% 3.6% % S % 4.40% 9.52% 3.6% % % 4.40% 9.52% 3.6% % % 4.40% 9.52% 3.82% % % 3.43% 3.55%.83% % 8.20% 6.30%.55%.28% % 9 0.8% 7.78% 0.55% 0.69% % Figur 7: Hirarchical Dcision Structur 366 Tabl 2: rnativ s priority

7 Prioritis 0 3% 3. 5% 5. 0% 0. % rnativ Figur 8: Final priority map for potntial altrnativs 4 Discussion and Conclusion: For a long priod, th concption of transportation planning modls has bn limitd by computational capabilitis. Basic oprations such as storag, organization and mathmatical manipulation wr oftn usd to procss a larg amount of data. Nvrthlss, thy could not contribut with nothing mor than this sinc th gographical-spatial rality was not possibl to b considrd du to a vry rstrict concption of databas for thos application. Consquntly, tools could not b dvlopd and modls stayd in a consrvativ stag, just manipulating numric data and gnrating a lot of rsults, which somtims wr maninglss. Th advnt of GIS and gradual dvlopmnt of a nw frontir is now possibl to b sn. Its rar capability to conduct spatial analysis can lad to th rduction of tim and mony in xploring a rich sourc of gographical-spatial data: RS. In addition, a nw gnration of transportation modls can b forsn in opposition to traditional approachs mor concrnd on th analytical procssing than th discussion and solution of problms. Along this dirction, it is ssntial to undrstand th potntial insid nw tchnologis such as GIS and to bring it togthr to dvlop fficint and consistnt valuations and modlling. This rsarch trid to follow prvious work carrid out by Yamashita t al. 23), which alrady showd promising rsults in trms of futur prspctivs. This papr rportd AHP-GIS-RS intgration as a hirarchical and gorfrncd approach to support dcision-making activitis. In this intgration, AHP contributs to procssing go-spatial data undr a dcision framwork combining th information and an intllignt fatur in th dcision procss. This intgration is conductd through th construction of thmatic maps gnrating a simpl and fficint instrumnt of analysis without any complx mathmatical formulations and procdurs. Spcifically about th dcision contxt, it lads to an valuation that can procss both qualitativ and quantitativ information, which ar usful to xtrapolat th concption of cost bnfit analysis. Th application of th intgration in a location problm provd to b a valid instrumnt to valuat aras to implmnt a DDC trminal. Th slction of potntial locations by itslf is vital not only bcaus it dfins a limitd numbr of altrnativs to implmnt th trminal, morovr it computs th most important factors influncing th dcision in a stratgic planning lvl. Hnc, it gnrats a satisfactory xplanation of th problm and a strong indication rgarding th bst location. It shows that if a plannr nds an instrumnt to dcid quickly and scurly about a location, this lvl of analysis can lad to vry intrsting rsult without consuming mor tim in furthr analysis. Bsids th succss of this application, it is important to highlight th larg varity of possibl dvlopmnts in othr problms. Th intgration of AHP-GIS-RS was dsignd to b gnral and applicabl in any typ of problm in transportation planning, sinc w wr mostly concrnd with th basic concption in opposition to spcific rquirmnts. In this sns, w hav workd in totally diffrnt applications such as attraction analysis of urban travls and rout dfinition for public transportation. Ths studis hav showd th fficincy and importanc of th AHP-GIS-RS intgration to solv traditional problms in day-to-day activitis of transportation plannrs. 367

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