Optimization Model in Human Resource Management for Job Allocation in ICT Project

Transcription

1 Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Saghamtra Mohaty Malaya Kumar Nayak 2 2 Professor ad Head Research Scholar Departmet of Computer Scece ad Applcatos Utkal Uversty Bhubaeswar 75 4, Ida E-mal Id: sagham@redffmal.com, malaya.au@gmal.com Abstract Ths research artcle hghlghts a ovel approach of schedulg rsk whch assures decrease cost ad crease performace for the huma resource maagemet Iformato ad Commucato Techology projects. The cost maagemet ca be cosdered as all the processes requred to esure that a project team completes ther assgmet wth a approved budget. Ths research paper wll focus o much bgger dmeso of problem cosderg varous dstrbuted factors project maagemet where all the ettes volved the project wll be cosdered for rsk schedulg. The proposed artcle wll provde support to dyamcally chagg evromets ICT ad also support ts complex heterogeeous evromet whch wll ehace the cost effectveess factor bgger scale project volved ICT. Keywords: Rsk plag, ICT, Cost estmato, Project plag, Huma resource maagemet. I. Itroducto Rsk cosequeces based o rsk maagemet actos are embedded sttutoal ad orgazatoal structure. Orgazatoal structure egages wth rsk maagemet through huma resource maagemet ad ts assocated securty ssues. Oe of the key reasos pot out by Matta ad Ashkeas [] s that maagers use project plas, tmeles ad budgets to reduce what we call executo rsk - the rsk that the desgated actvtes wo t be carred out properly but evtably eglect these two other crtcal rsks the Whte Space Rsk that some requred actvtes wo t be detfed advace, leavg gaps the project pla, ad the Itegrato Rsk that the dsparate actvtes wo t come together at the ed. Ofte project maagers do ot have ay rsk cost estmato Staw ad Ross [2] ad whe the project cost grows way beyod budget, they do aother mstake whch s stated by Davs [3]. Ad oe of the toughest parts of project maagemet s maagg huma resource effectvely. Hughes [4] further clams that maagg ICT rsks must focus o a combato of process, people, techology ad formato. It also detfes the huma resources requred to mplemet the pla. Leve [5] also supports the vew that ICT rsk maagemet must take to accout people, process ad systems, cludg orgasatoal factors such as corporate culture ad employees. 2. Rsk Schedulg ICT Rsk assessmet ICT project s very crucal wth respect to huma resource maagemet. Certa ssues employee rsk schedulg are loss of productvty for skll gaps them for whch reaso the Iteratoal Joural of the Computer, the Iteret ad Maagemet Vol. 9. No.3 (September-December, 2 pp

2 Saghamtra Mohaty ad Malaya Kumar Nayak assgmet allotted could ot be accomplshed effcetly. Iadequate requremet aalyss of project s aother ssue whch makes eve the project maager dffcult to uderstad the real requremets of clet, for whch reaso the project maager fals to detfy hs best team ad thereby mproper project load allocato proceeds ahead gvg rse to other tertary ssues. Sudde attrto rate s aother ssue for whch the project maager has to maage the project developmet wth hs exstg team. Normally ICT rsk schedulg s rooted corporate plag ad audt system whch are majorly deployed as a secto of the rsk maagemet ay orgazato [6]. However, t s observed that such types of rsk schedulg methodology are much cocetrated o varous parameters whch have the potetal to leverage busess requremets. 3. Proposed Model The proposed model wll be based o the curret ssues support of rsk schedulg ICT projects where the cocer s more about huma resources. Majorty of the curret researches are focused geeral rsk maagemet schemes whch maly mplemets ISO3 stadards whch ormally facltates oly geerc gudeles for the desg, mplemetato ad mateace of rsk maagemet processes throughout a orgazato [7]. The ICT structure, as a top-dow strategy, s represeted the COBIT framework whch s extesvely used to descrbe the busess fuctos, processes ad tasks to support top maagemet developg ad mplemetg ICT goverace [8]. By adoptg COBIT, the orgazato s cocered more wth a busess vew tha wth techcal solutos to ICT rsk maagemet. Ths rsk schedulg process seeks to fd a optmal allocato of a lmted amout of resource to objectves subject to the gve resource costrat. The best or optmal soluto may mea maxmzg profts, mmzg costs, or achevg the best possble qualty. The algorthm used proposed system s well explaed the secto 4 ad the mathematcal emprcal model s explaed secto Algorthm Descrpto The proposed algorthm s based o the mathematcal optmzato model wth a motve to assst the project maager selects hs best team from dfferet sklls wth hgher proft ad cost-effectve measures. Applyg the mathematcal optmzato, a objectve fucto s cosdered for project maager whch bascally represets the requremets of selecto of optmzed plas for rsk schedulg ad cost-effectve joballocato to hs exstg resources effcetly. Ths objectve fuctos of real ature eed to be optmzed smultaeously mult-objectve optmzato problem for maager towards plag of rsk as cost estmato. It s ot requred that there has to be exstece of soluto whch s best to all objectve due to commesurablty ad coflcto amog objectves. So, the outcome of ay such computato may vary from best oe objectve but may be worst aother objectve. Therefore, there usually exst a set of solutos for the multpleobjectve case whch caot smply be compared wth each other. For such Pareto optmal solutos, o mprovemet s possble ay objectve fucto wthout sacrfcg at least oe of the other objectve fuctos. Usually, our rsk schedulg problem ca be represeted as: m y = f(x = (f (x, f 2 (x,..., f (x, (- s.t. g (x. Where admstratve vector x R m where R 22

3 Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project s real value, ad targeted vector y R, f (x( =,2,..., s the objectve fucto, g (x s a boud codto. Ths represetato hghlghts the project maager has a varous alteratve varables (x as problems whch eeds to be solved uder certa boud codto. Theorem-: If x* R m s represeted as a posto the search space; f ad oly f there s o ( the search space makg f (x<f(x* establshmet, the x* s the odomated soluto. Theorem-2: Assumes u, v R m, f ad oly f vectors meet wth, f ( u f ( v {,2,..., }; (-2 f j ( u f j ( v j {,2,..., }; (-3 The fucto f wll deped o the skll ssue of the employees. The vector u domates vector v, deoted as u v. Theorem-3: For a gve dvdual x P, f there s o dvdual makg y x establshmet, the x s called the odomated dvdual. All the P s odomated dvdual cosst the set whch s called the domated set of P. 5. The Mathematcs Model The emprcal model for the dversfed skll crtera huma resource allocato problem to assg M staffs to dfferet posts for maxmzg the beeft ad mmzg the cost subject to oe huma resource costrat s desged as follows: max z (y = f ( (2- = y m z 2 (y = f ( (2-2 = 2 y s.t. G o (y = g ( y M (2-3 y =,,..M (2-4 Accordg to the above metoed mathematcal represetato (2-, (2-2, (2-3, (2-4, the research work ca be desged for rsk schedulg cosderg multple huma resources wth dfferet avalable sklls optmzato model. Ths model s a map of crtera for resource allocato ad costg problems of the maagers, whch wll ow eable the M set of employees to varetes of jobs for cremetg the beefts as well as reducg the cost mposed to oe set of huma resource costrat. Therefore, a teger programmg model for multple specfcatos ca be modeled as below: max z (x = p j x j m z M = j= M 2(x = = j= c j x j (2-5 (2-6 α l ( d dl Dj Pj = V x x (2-7 d D l j max αl ( d dl c j =W x (2-8 d M l s.t. G (x = jx j M (2-9 G x j = = j= (x= x j =, (2- α ( d l dl d l, (2- = or,, j (2-2 Notato Used: V = value of the th post, (j=, 2,..., ; α l s the weght of the th post s (: dex for departmet wth parameter N total umber l th skll competecy; (j=, 2,.,; l=,2,...; Iteratoal Joural of the Computer, the Iteret ad Maagemet Vol. 9. No.3 (September-December, 2 pp

4 Saghamtra Mohaty ad Malaya Kumar Nayak d s the level of the j th post s (j: dex for employees wth parameter M total umber l th skll competecy; (l=,2,..m; l d 9, d 9, d N ; dl s the referece level of the th post l th competecy;(l=,2,...m; l d 9, d N ; skll D j s the Maager s expectato level of the j th staff to th post. ( l d 9, d N ; D j max s the hghest level of the j th staff to all posts; W s the remuerato / wage of the th post. C j s cost of departmet whe j employees are assged Pj s proft of departmet whe j employees are assged. 5. Huma Resource Optmzato We dvde a evoluto groups to several sub-groups wth several dfferet evolutoary drecto, ad the defed the domated relatoshp of dvduals usg the cocept of o-domated soluto. The we ca formulate a o-domated set wth the o-domated optmal partcles whch s foud each subgroups. The global optmum rego whch s costtuted by odomat dvduals gudes the evoluto of whole partcle group. The algorthm ca obta Pareto soluto set of dstrbuted uformly through less tmes terato. I order to use the huma resource optmzato wth respect to cost evaluato order to desg wth rsk schedulg, we eed to formulate certa specal operatos to gude the evoluto of search process, or adopt the strategy of ftess taxs to acheve t. Ths paper presets the followg defto: Say x s a dvdual of group S, f (x(t s x s value of the th objectve fucto value whe s o the th tmes teratos. Theorem-4: I the teratve process, f the value of x to all objectve fuctos vares to be optmal, the x may be termed as etre optmal employee for ths tmes teratve process. S+ deotes the group whch s made up of all etre optmal employees, ad that s: f (x(t + < f (x(t, {,2,...,}. (3- Theorem-5: Sometmes teratve process, f the value of x to oly oe objectve fucto vares to be optmal, the x s called the half optmal employee for ths teratve process ths drecto of the objectve fucto. S k deotes the group whch s made up of all half optmal dvduals, ad that s: f k (x(t + f k (x(t, k {,2,...,}. (3-2 Theorem-6: Sometmes partcular teratve process, f the value of x to all objectve fuctos vares to be feror, the x s called the etre feror employee for ths teratve process. S deotes the group whch s made up of all etre feror employees, ad that s: f (x(t + >f (x(t, {,2,..., }. (3-3 Theorem-7: Assume x ad y s ay two employees of group, x domates y whe they meet wth the followg codtos. x s ot feror tha y to all objectve fuctos, that s f (x f ( y, {,2,...,}. (3-4 2 There s oe objectve fucto at least makg that x s better tha y, amely: f k (x< f k ( y, k {,2,...,} (3-5 The research put forward the method that usg multple sub-groups esured the multple evoluto drecto of the etre group. The we ca determe the domat 24

5 Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project relatoshp betwee the employee the sub-groups. 5.2 Cost Estmato I order to use the algorthm, the applcato must code for the soluto of the problem frstly. It ca smply use the order of atural umber ~ to preset a potetal soluto. Assume the posto vector of the th departmet s X = {x, x 2,...x } whch presets the result of the huma resource allocato. Of whch x j s the umber of employee for the j th post wth the scope of orgazato. The approach took the huma resource allocato problem ICT projects of 4 posts for example. The outcome of oe posto vector s = (4.2, 3, 2.3, 6.. After the tegral orms treatmet the outcome s (4, 3, 2, 6. The optmal soluto of the huma resources allocato s that the 4 th staff s allocated o the frst postos; the 3 rd staff s allocated o the secod postos; the 2 d staff s allocated o the thrd postos; the 6 th staff s allocated o the fourth postos. Such allocato desg wll help the maager to pla the cost estmato of the avalable sklled employees for rsk schedulg the orgazato. 5.3 Rsk Schedulg Methodology The sklls requred Iformato Socety volve the capablty to deploy ICT resources to mplemet varous dyamc e- govermet strateges of a orgazato accordace wth ts overall rsk schedulg. Such types of sklls wll volve aalyzg varous ovatve techologes ad ther lmts alog wth the corporate s rsk plag wth respect to huma resource maagemet. Referecg for the multobjectve optmzato method, ths research paper desgs the process of the multobjectve optmzato of huma resource allocato wth effcet performace, descrbed as follows: Step: Italze optmzato, cludg populato sze N, the locato of varous ettes lke departmets x wth speed v ; Step2: Estmate the ftess value of each objectve fucto; Step3: Backup ftess value; Step4: Retreve the tal pbest ad gbest usg weght; Step5: Update departmets accordace wth stadard optmzato algorthm; Step6: Dvde the group to four sub-groups accordg to Theorem 4-6; Step7: Accordg to Theorem-7 fd the global optmum rego, ad get a ew dvdual extreme value ad the global extreme value, ad the update the etre feror sub-groups; Step8: Update the speed v ad posto x of every partcle wth the gbest ad pbest Step7; Step9: If meet the suspeso codtos, the crcle stop; otherwse retur to Step6. 6. Calculato A compay wll expad ts busess exteso. For example, the compay has set up 4 ew postos. The compay decdes to choose 4 staffs from four sectors; each sector selects a sutable staff. Each ut has 2 employees, totally 48 people. Supposg that we do ot cosder other specal factors, we should allocate these staffs to 4 ew postos wth the target of maxmum beeft ad mmum cost. After dealg wth the data wth formula (2-7-ad (2-8, we ca obta the cost ad proft data of each employee varous postos whch s preseted Table. We ca get a satsfactory result wth the algorthm whch has bee valdated by may Iteratoal Joural of the Computer, the Iteret ad Maagemet Vol. 9. No.3 (September-December, 2 pp

6 Saghamtra Mohaty ad Malaya Kumar Nayak tmes expermet. Table I. The Proft ad Cost of Staffs Past 4 Years Ut- Ut-I Ut-II Ut-V X cost proft X2 Cost Proft X3 Cost Proft X4 cost proft X 93 3 X2 9 4 X X X X X X X X X X X X X X X5 6 X X X X X X X X X X X47 47 X8 5 9 X X X X X X X X 3 79 X2 2 7 X X X X X X X2 2 7 X X X X 7 X2 4 X3 6 X4 2 Table II. The Optmal Pareto Solutos Solutos Desgato- Desgato Desgato Desgato Cost Proft d> k After performg the above evaluato, calculate the geeratoal dstace value from oferor solutos to the optmal Pareto solutos through geeratoal dstace method. Accordg to calculato of the geeratoal dstace value, we ca obta the optmal soluto of ths problem. The optmal soluto s: X = {2,7,,2}. So the maager should select the 2 th employee to desgato ut ; select the 7 th employee to desgato 2 ut 2; select the st employee to desgato 3 ut 3; select the 2 d employee to desgato 4 ut Cocluso Ths research artcle appled the competecy model ad posto assessmet ad employee s expectato to determe sythetcally the proft of some employee o some post whe we developed the mathematcal model of mult-objectve crtera huma resources allocato whle rsk schedulg ICT project. Ths method embodes the double prcples of staffs competecy matchg wth posto request ad staffs expectatos matchg wth 26

7 Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project posto, whch accord wth the actual stuato of huma resource maagemet. Refereces [] Matta, Nadm F ad Ashkeas, Roald N. (25, Why Good Projects Fal Ayway Harvard Busess Revew o Maagg Projects 25. Harvard Busess School Publshg Corporato. [2] Staw, Barry M. ad Ross, Jerry (25, Kowg Whe to Pull the Plug Harvard Busess Revew o Maagg Projects 25, Harvard Busess School Publshg Corporato. [3] Davs, Davd (25, Beware of False Ecoomcs Harvard Busess Revew o Maagg Projects 25. Harvard Busess School Publshg Corporato. [4] M, Cotterall, ad B, Hughes (26, Software Project Maagemet (Fourth Edto ed.. Berkshre, UK: McGraw - Hll Educato. [5] R, Leve (24, Face ad Growth: Theory ad Evdece, Workg Paper Seres-NBER. (766. [6] Speklé, R. F., Elte, H. J. V., ad Kruts, A.-M (27. Sourcg of teral audtg: A emprcal study, Maagemet Accoutg Research (8, pp [7] P., Grat (2, ISO 3:29 Settg a New Stadard for Rsk Maagemet, Wley Ole Lbrary, Volume 3, Issue 6, pages , Jue. [8] Robso, N (25. IT excellece starts wth goverace, The Joural of Ivestmet Complace (6:3, pp Iteratoal Joural of the Computer, the Iteret ad Maagemet Vol. 9. No.3 (September-December, 2 pp