ScienceDirect. ZHANG Lili* a,b,c. An Inverse Optimization Model for Human Resource Allocation Problem Considering Competency Disadvantage Structure

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1 Avalable onlne a ScenceDrec Proceda Compuer Scence 2 (207) An Inverse Opmzaon Model for Human Resource Allocaon Problem Consderng Compeency Dsadvanage Srucure ZHANG Ll* a,b,c a School of Busness, Dalan Unversy of Technology, Panjn 2422, Chna b School of Sysems Engneerng, Dalan Unversy of Technology, Dalan 6024, Chna c Dalan Unversy of Technology-Bejng research nsue, Bejng00000, Chna Absrac Mos of serous and major accdens ha happened durng he producon procedure of process ndusry are caused by mproper equpmen operaons, whch s furher owng o napproprae human resources allocaon and gnorance of ndvdual compeences dfferences. In order o ake boh of compeency dsadvanage and adjusmen requremen no consderaon, we use an nverse opmzaon mehod o solve a human resource allocaon problem, and furhermore, adjus equpmen operang parameers o make he per-defned sengs opmzed, such as he oal number of jobs, secury-relaed parameers and so on.in he solvng process, frsly a sandard compeence herarchy sysem s conduced; secondly we propose an assessmen mehod accordng o dsadvanage srucure; hrdly we use nverse opmzaon mehod o solve he problem and opmze he predefned allocaon plan. Lasly, we gve an example o prove s feasbly and effecveness. In hs paper a novel formulaon of human resource allocaon problem s proposed, n whch some of man ndvdual characerscs are consdered and descrbed mahemacally, ncludng psychology, behavour and characerscs dged from hem such as weakness. The oher conrbuon of hs paper s usng nverse opmzaon o adjus parameers based on he gven deal allocaon plan. Boh of hese proposons have a posve sgnfcance on promong developmen and secury consrucon for process ndusres.ths research ncorporaes he academc hnkng of nverse opmzaon, no only pus psychology and behavor no opmzaon model, bu also daa mnes weakness characerscs under he psychology and behavor daa, and fnd a new way o nroducng he weakness characerscs no decson makng model. I provdes a new hough for he followng decson makng problem, ha s he deal decson plan s known, and opmzaon parameers are changeable. I promoes he combnng of psychology, behavor and operaons research, s good for process ndusres o develop n a safey and effcency way. 207 The Auhors. Publshed by Elsever B.V. Peer-revew under responsbly of KES Inernaonal Keywords: nverse opmzaon; lnear programmng; human resource allocaon; compeency; evaluaon accordng o dsadvanage srucure * Correspondng auhor. E-mal address: llzhang@dlu.edu.cn The Auhors. Publshed by Elsever B.V. Peer-revew under responsbly of KES Inernaonal 0.06/j.procs

2 62 ZHANG Ll / Proceda Compuer Scence 2 (207) Inroducon Process ndusry ncludes perochemcal ndusry, ron and seel ndusry, nuclear power ndusry and so on. All of hses process ndusres are very mporan o he developmen and secury of he counry. Process ndusres parly deploy connuous producon, he manufacurng process always goes wh a seres of physcal changes and chemcal reacons, whch makes he whole producon process very dangerous due o s nflammable and explosve properes. so secury s he frs concern for he whole equpmen and human resources managemen n process ndusry. The producon safey degree manly reles on human resources compeency wh consderaon of dsadvanage, and mos mporanly, depends on he allocaon of human resources. The equpmen operaon compeency always mples specfc characerscs ha dfferenae compeen operaors from poor or normal ones. Compeency managemen research of process ndusres sll lag behnd n he realy need. Ths ssue s mos noceable a he human resources allocaon and adjusmen plannng level. Human resources allocaon of process equpmen s nclned o use mahemacal opmzaon mehods, such as lnear programmng, nonlnear programmng, mul-objec programmng, combnaoral opmzaon, neger programmng, apply hese models o acheve he bes economy benef under he consrans of workload needed wh consderaon of effcency. Furhermore, mos of he human resources opmzaon mehods propose an opmzaon model under he condon of he known cos parameers, workload parameers, effcency parameers, hrough some algorhm, o deermne he value of decson varables( for example resources allocaon plan), o acheve he goal of cos as small as possble or he prof as large as possble. There are some parcular characerscs of equpmen operaors, frsly, work effcency depends on compeency; secondly, equpmen operaon sysem secury follow he "cask prncple", an equpmen operaon sysem's safey depends on he weakes pon whch s worker's comprehensve evaluaon of compeency accordng o he dsadvanage srucure. In erms of exendng cask prncple, wh consderaon of equpmen safey operaon, we defne work effcency parameer n he opmzaon model as he average compeency evaluaon resul accordng o dsadvanage srucure. Dsadvanage srucure s defned as he evaluaon wegh vecor whch can make he objec acheve wors resul. Also accordng o he characerscs of human resources, we negrae behavoral facors and psychologcal facors no opmzaon model. However, n realy, somemes he human resources allocaon plan s deermned, for example, he plan s an order from he op leader, under he pressure of human resources reform such as cung down he number of person employed, so he resources allocaon decson has o follow he order. Then hs s a pre-se plan-drven human resources allocaon problem, hs problem has been on he rse n resources managemen pracce. Also n he real world, human resources allocaon problem always face he challenge on revealng unknown or mplc parameers n decson-makng processes. Bu we can esmae parameers wh experences. In order o solve hs knd of problem, he decson maker needs o change some of he model parameers o make he predefned resources plan he opmal soluons under he new parameers. Ths problem s hrough adjusng opmzaon model parameers o make he pre-se plan be he opmal soluons. All hese problem feaures agree wh he defnon of nverse opmzaon. Inverse opmzaon consss of fndng a mnmal adjusmen of he parameers such ha a gven se of feasble soluons become opmal. Especally, behavor and psychology feaures are very mporan o equpmen operaon safey, so n hs work, an nverse opmzaon model s developed for allocang human resources o dfferen jobs wh consderaon of psychology and behavor feaures. The adjused parameers refers o he work load parameers. The cos parameers are deermned accordng o average salares, he effcency parameers are deermned by he comprehensve compeency evaluaon accordng o dsadvanage srucure. The decson varables express he number of personnel allocae o dfferen job groups.

3 ZHANG Ll / Proceda Compuer Scence 2 (207) The paper s dvded no four man secons. The nex secon provdes a leraure revew, secon 3 proposes a compeency ndcaor model of equpmen operaon personnel and consruc a comprehensve evaluaon model based on dsadvanage srucure. Secon 4 proposes he nverse opmzaon mehod for human resources allocaon wh consderaon of psychology and behavor. To my bes knowledge, hs paper was he frs nsance usng he nverse opmzaon approach for human resources allocaon wh a focus on deermnng he mplc value assocaed wh he compeency condon, and n order o make he dea plan o be he opmal soluon afer parameer revsed. The las secon s o propose an applcaon example o demonsrae he relably and feasbly. 2. Leraure revew () Compeence model and evaluaon leraure revew:there are many sgnfcan research on compeence models Compeences refer o he combnaon of knowledge, skll, moraly, deas and so on. Compeence s defned from dfferen perspecves such as general compeences, sof sklls echncal compeences. Wh he developmen of mulvarae analyss mehod, compeency modellng has a sandard framework and mehod. Furhermore, compeency models have been developed wdely used o denfy compeences requred o perform a specfc job effecvely n an organzaon. The compeency ncludes: delvery-relaed compeences, nerpersonal compeences, sraegc compeences, communcaon sklls, resource-nformaon-echnology processng and applcaon sklls, nerpersonal and cooperave sklls, global compeency, comprehensve hnkng compeency, self-managemen compeency, readng for nformaon compeency, appled mahemacs compeency, problem solvng compeency, crcal hnkng compeency, managng personal and nerpersonal relaonshps compeency, communcaon compeency. The compeences relaed o safe operaon ncludes: perceved suscepbly, perceved sever, perceved benefs of akng acon, perceved barrers o akng acon cues o acon, selfeffcacy []. Compeency evaluaon s he foundaon of compeency-based human resources allocaon. There are los of evaluaon mehod developed n recen years. There has been wld research on quanave mehods, for example: AHP mehod, DEA mehod, Mxed-Mehods, Fuzzy AHP, Evaluaon accordng o srenghs, evaluaon from a mullevel perspecve. Evaluaon mehod s always along wh specfc problem, accordng o he characerscs of he problem, he specfc evaluaon mehod s proposed. (2) Human resources opmzaon leraure revew:there are los of progress on he research of human resources opmzaon mehod. Such as op-down and boom-up approach [2]. 0- assgnmen model [3]. mulprojec human resource allocaon based on he negoaon mechansm wh consderaon of oal cos consran and ndvdual dscplnes [4]. call cener human resource allocaon model accordng o M / M / N + M queung model [5]. four-n-one personnel machng mehod based on advanage srucure [6]. fuzzy npu-oupu opmzaon model [7]. opmal human resource managemen model wh consderaon of oal uly level or cos npu condon [8]. (3) Human resources opmzaon leraure revew:there are manly wo knds of nverse opmzaon problems, he general nverse (reverse) opmzaon problem and nverse opmal value problem, each knd of problem has been researched from he perspecve of modelng, algorhm and applcaon. Generally, nverse opmzaon s gven an deal soluon, n order o make he deal soluon be he opmal soluon, hrough adjus he orgnal model parameers as small as possble and mee he demand of he deal soluon opmal. The research manly focus on he followng problems: ) Under some specfc assumpons, he demonsraon of he exsence of opmal soluon; 2) he conver mehod from forward opmzaon, such as lnear programmng model, mulobjecve programmng, assgnmen model, nonlnear programmng, mach problem and so on. Accordng o he

4 64 ZHANG Ll / Proceda Compuer Scence 2 (207) mahemacal characerscs of each programmng model, he conver mehod of each ype of opmzaon model has been suded. And dfferen opmzaon algorhms and evoluonary algorhms o solve dfferen nverse opmzaon models. From he perspecve of applcaon research, mos of he applcaons are used for esmaon of parameers n he orgnal opmzaon model. Such as gven a lnear program, a desred opmal objecve value or decson plan, and a se of cos vecors, resources vecors, effcency marx, one needs o deermne a cos vecor of he lnear program such ha he correspondng opmal objecve value s closes o he desred value or desred decson plan. The represenave achevemens are: shores pah nverse opmzaon problem [9]. resrced nverse opmzaon model wh a value coeffcen no allowed o adjus [0]. generalzed nverse opmzaon model of lnear programmng for opmal producon plannng []. nverse opmzaon model of lnear programmng on logscs cener []. nverse opmal allocaon model n grd envronmen [2]. nverse opmzaon for secury resource allocaon [3]. nverse lnear programmng model of nerval coeffcen [4]. nverse opmzaon mehod o deermne heang mode [5]. nverse packng problem [6]. nverse opmzaon of supply chan resources [7]. secury resource allocaon [3]. porfolo selecon hrough nverse opmzaon [8]. nverse daa pack analyss of he froner changes of arge seng " [9]. There are los of researches on he opcs of human resources managemen, comprehensve evaluaon mehod and nverse opmzaon mehod, hese researches gve hs sudy a lo of enlghenmen. However, so far as we know, here s no research whch combnes compeency, dsadvanage srucure and nverse opmzaon ogeher, and he combnaon s very mporan for equpmen operaon safely n process ndusres. So we focus on dsadvanage compeency-based human resource nverse allocaon mehod. Ths research ncorporaes he academc hnkng of nverse opmzaon, and no only pus psychology and behavor parameer no opmzaon model, bu also denfy dsadvanage srucure under he psychology and behavor daa, and fnd a new way o nroducng he dsadvanage characerscs no opmzaon model. So we sudy he above problem, s benefcal for broadenng he research mehods of decson makng problems; promoes he combnng of psychology, behavor and opmzaon research, s good for process ndusry enerprses balance safey and benef, s good for process ndusres o develop n a healh way. 3. Equpmen operaor compeency evaluaon accordng o dsadvanage srucure The comprehensve evaluaon mehod conans hree pars: () consruc a compeency ndcaor sysem; (2) consruc a dsadvanage srucure denfcaon model; (3) consruc a comprehensve model based on dsadvanage srucure parameers. 3.. Equpmen operaon compeency ndcaor sysem We consruc a compeency ndcaor sysem o mprove equpmen operaon safey n process ndusry from a human-cenered perspecve. Equpmen operaon compeency model descrbes a sasc analyss resul. I can be used odsngush hghly effecve workers from ordnary or low performance workers. The formaon of equpmen operaon compeency ndcaor sysem follows hree seps belowas menoned n relaed leraures : bran sorm mehod and Delph Mehod, analyss of he quesonnare's relably and valdy. The quesonnare was conduced on 244 employees randomly seleced from hree dfferen process ndusry companes. A oal of 500 persons were approached and 256 reurned. Afer removng 2 ncomplee quesonnares, we obaned a sample of 244 respondens. We measured all he varables consdered wh mulple-em scales. We use Lker scale mehod o measure he level of agreemen. We use a srucural equaon model approach wh AMOS sofware. We esed he relably of each consruc by usng Cronbach's Alpha. To es he convergen valdy of he measures, we examned he sgnfcance of he facor loadng o prove relably.the KMO and Barle s shown n able.

5 ZHANG Ll / Proceda Compuer Scence 2 (207) Table Compeency of KMO and Barle Kaser-Meyer-Olkn.960 approxmae ch-square Barle vale df 653 Sg..000 The regresson coeffcen of measuremen model of equpmen operaor compeency s shown n able 2. Table 2 Regresson coeffcen of measuremen model pah ndcaors regresson facor S.E. C.R. P coeffcen Sandard pah coeffcen collaboraon <--- psychology ac decsvely <--- psychology ***.833 sharng <--- psychology ***.849 self-conrol <--- psychology ***.8 deal orened <--- aude logc <--- aude ***.869 professon <--- aude ***.860 responsbly <--- aude ***.803 problem solvng <--- skll sysemac hnkng <--- skll ***.875 nnovaon ably <--- skll ***.804 rsk managemen <--- skll ***.873 analycal sklls <--- skll ***.80 echnology <--- knowledge mechansm <--- knowledge ***.872 producon process <--- knowledge ***.847 auomac sysem <--- knowledge ***.870

6 66 ZHANG Ll / Proceda Compuer Scence 2 (207) Compeency evaluaon mehod accordng o dsadvanage srucure Defnon: dsadvanage srucure s he evaluaon ndcaor wegh vecor, whch s based on he evaluaon compeency sysem, accordng o he evaluaon objec s acual ndcaor value, consruc an opmzaon mehod, he decson varable s wegh vecor, he objecve s o ge he wors evaluaon resul of he evaluaon objec, he parameer s evaluaon ndcaor value. Symbol descrpon: Compeency evaluaon model s expressed by a hree layer ndcaor sysem. The op level s compeency z, he mddle level compeency ndcaor s y, =, 2,,, m, whch means y,,, y y, he wegh vecor s µ, =, 2,,, m µ,,, µ µ. y m conans basc ndcaor basc evaluaon ndcaor evaluaon wegh vecor s 2 x, x,, x. m 2 p y conans basc ndcaor 2 x, x,, x p ; y conans 2 x, x,, x, correspondng m m mp m l, l,, l.compeency sysem can be expressed as fgure. m m mp m m compeency z psychology y aude y knowledge ym Collab oraon x Ac Self Deal Logc Orened Responsbly decsve Technology conrol Mechansm Process x 2 x p x x 2 x p x m x m2 x mpm Fgure : Equpmen operaon compeency ndcaor sysem () Dsadvanage srucure denfcaon mehod of mddle level denfcaon mehod accordng o he basc level ndcaor value. (, k) (, j) p ( (, )- (, )) = å( l(, )) ( (, )- (, )) 2 (, k) *+ (, k) (, k) 2 *+ (, k) 2 j j j j j j= mn d x x x x l p (, k) å l(, j) = () j= s.. l ³ 0 j =, 2,, p The objecve mnmzes oal compeency benefs. Subjec defnes he wegh resrcon. x *+ (, j) s he posve deal value of ndcaor, for example, f he value s expressed by Lker fve scale mehod, *+ (, j) x equals o 5.

7 ZHANG Ll / Proceda Compuer Scence 2 (207) x (, k) (, j) s ndcaor value, whch s an known value by 360 degree apprasal law. (2) Compeency evaluaon n he mddle level accordng o dsadvanage srucure y s model(2). ì =0; f x ¹ x y í = å î j= * ( ) (, ) *+ (, ) ( l ) ( ) (, j x ) (, j - x ) (, j ) p *+ 2 k k 2 ; oherwse (2) When all he basc ndcaor of he h mddle level ndcaor s deal, he value of y s 0. Oherwse, he value of y s calculaed accordng o dsance funcon. (3) Dsadvanage srucure denfcaon mode from he op level. 2 2 (, k) * (, k) (, k) (, k) - = - mn d ( y y ) d (0 y ) µ m P * (, k) 2 (, k) 2 * (, k) 2 å( µ ) å( l(, j) )( x(, j) x(, j) ) = j= = - m (, k).. å µ = = s µ (, k) ³ 0 =, 2,, m (3) ( k, )* µ s he dsadvanage srucure denfcaon resul.the objecve mnmze oal compeency benefs. Subjec defnes he wegh resrcon. * * y s he posve deal value of ndcaor, n hs case y equals o 0. ( k, )* µ s opmal soluon, represens dsadvanage wegh parameer of he mddle level. (4) Compeency evaluaon mehod based on dsadvanage srucure The value of op level compeency ndcaor s calculaed accordng o model (4). m m * 2 * 2 * 2 2 å µ () å µ = = Dz ( ) = ( ) ( y - Dy ( )) = ( ) ( Dy ( )) = ( )[ ( )( ) ] m n p * 2 * 2 * (, k) 2 2 å µ å å l(, j) x(, j) - x(, j) = n = j= (4)

8 68 ZHANG Ll / Proceda Compuer Scence 2 (207) The average resul of each personnel a each job s he effcency parameer value. 4. Inverse opmzaon of human resources allocaon based on compeency dsadvanage srucure Oppose o he forward mnmze cos approach, an nverse approach was underaken o nfer he values of model workload parameers o make he desred human resources allocaon plan he opmal soluon under new parameers. Human resources opmzaon problem s o deermne he values of decson varables such ha he objecve funcon can ge he opmal value on he condon ha all parameers are gven n he opmzaon model of objecves and consrans. In hs research, effcency parameer value s calculaed accordng o compeency evaluaon accordng o dsadvanage srucure. The cos parameer s calculaed accordng o human resources salares and he enerprse acual suaon. The consran parameers are oal workng hour need for each job. The objecve funcon of opmzaon s he make he cos as small as possble. The decson varable s workng hours allocaon plan of each knd of human resources o each knd of job. 4. Forward opmzaon model of human resources opmzaon The necessary and funcon of he orgnal model are he follows: ) s a descrpon of he specfc human resources allocaon problem, n he orgnal model, we do no care wheher he opmal soluon has an acual meanng or he parameers are known, we jus wan o gve a descrpon of he human resources sysem; 2) s a basc model of converng, whch means he sarng pon for nverse opmzaon. The general opmzaon model s as followng model(5), The sandard model s he bass for converng he orgnal model, because he converng mehod s accordng o dual heory, so f we gve he sandard model, s convenen for converng: mnz = f( x) s.. x ÎW n { x R A( x) 0, E; A( x) 0, } W = Î = Î ³ ÎG (5) In order o smplfy he problem and also accordng o he nvesgaon, we consruc a lnear programmng model, can be formulae as model(6). mnz = n å j= cx j n ì å ax j j ³ b, =,..., m s.. í j= îxj ³ 0, j =,..., n j (6) Theren, he decson varables are x, he cos vecor s c, he effcency parameer s a, he resource vecor j b, and b ³ 0, he objec s o make he human resources cos as small as possble. There are n jobs, m human resources. j j

9 ZHANG Ll / Proceda Compuer Scence 2 (207) Inverse opmzaon model converng mehod Accordng o he opmzaon model of problem descrpon, choosng adjused parameers, n hs case we change work load parameer as small as possble, Afer all hs, we can acheve he goal of he new human resources allocaon plan mees he requremen of reform, and make he plan guaranee he compeency sasfy he requremen of operaon safey and relable, also can mee he cos requremen. The solvng mehod of he nverse opmzaon depends on he mahemacal characerscs of he nverse model, dfferen nverse opmzaon models need dfferen solvng mehods. We use Lngo o solve he orgnal model for he followng reasons: ) we wan o compare he resuls wh nverse opmzaon model. Dual model s heorecal bass for converng from forward model o nverse opmzaon model. Accordng o dual heory, he nverse opmzaon s (7) and (8). Inverse human resources opmzaon consss of fndng a mnmal adjusmen ofb such ha a gven se of feasble soluons becomes opmal. When we adjus b The nverse opmzaon model s:, mn b- b ì ax. ³ bw, = 0 s.. í î ax. = bw, > 0 (7) b Le = b + s - b,,2,... m =, s ³ 0, b ³ 0 s - b s -b mn s + b,model (7) equals o model(8) ìax. - s + b ³ bw, = 0 s.. ía. x- s + b = b, w > 0 s, b ³ 0, =,2,... m î (8) 4. Case sudy An nverse opmzaon problem can be descrbed as follows: Gven an opmzaon problem(whch s orgnal opmzaon model) and a feasble soluon o, he correspondng nverse opmzaon problem consss of fndng a mnmal adjusmen of he vecor such he gven soluon becomes opmum. In correspondng o model(6), we defne he adjused parameers B are he work load parameers. The cos parameers C are deermned accordng o average salares, he effcency parameers A are deermned by he comprehensve compeency evaluaon accordng o dsadvanage srucure. The decson varables X express he hours of each knd of human resources allocae o dfferen job groups. There are 4 knds of jobs, here are 3 knds of human resources, he cos vecor for each knd of human resources sc=(5,0,20),he oal work load needed B=(7,6,9,8) T, he forward opmzaon problem s modeled as expressons (9).The frs X s calculaed accordng o he orgnal model, s he opmal soluon of he orgnal

10 620 ZHANG Ll / Proceda Compuer Scence 2 (207) model. The x s a pre-se resources plan, s a gven soluon, s gven by he auhory, s no a calculaed resul. mn Z = 5y + 0y + 20y 2 3 ì3x + x2 ³ 7 2x2 + 3x22 + 4x23 ³ 6 x32 + 3x33 ³ 9 2x4 + 2x43 ³ 8 í y = x + x + x + x y = x + x + x + x y = x + x + x + x î xj ³ (9) Usng Malab o solve model (9), he opmal soluon of model (9) s: é2 0ù ê 3 2 ú X = ê ú, Y = ( 7,6,5 ), Z = 265 ê0 3 2ú ê ú ë2 0 2û In praccal applcaons, gven he soluon (), he decson maker need o make () he opmal soluon accordng o realy concerns. X * é3 0ù ê 3 2 ú = ê ú ê ú ê ú ë2 0 û We use nverse opmzaon o adjus B. Then he nverse opmzaon model s as follows: mnq + q + q + q + a + a + a + a ì9+ - q+ a ³ q2 + a2 ³ 6 í q + 3 a ³ q + 4 a ³ 4 8 î q, a ³ 0, =, 2,3, 4 To solve model(2), he opmal soluon s q = ( 3,0,0,0 ) T, a = ( 0,0,0, 2) T (0) () (2)

11 ZHANG Ll / Proceda Compuer Scence 2 (207) Under he above parameers, he opmal soluon of model (2) s * X, Y ( ) = 8,6, 4, Z = 260 Through he case sudy, we ndcae ha accordng o he forward opmzaon model(9), a gven soluon (), hrough nverse opmzaon by adjus B as mnmum as possble, we can ge a beer resul ( ) Y = 8,6, 4, Z = Conclusons Y ( ) han he orgnal opmzaon problem = 7,6,5, Z = 265 Ths sudy adops he lnear programmng mehod o a human resources allocaon model wh consderaon of compeency dsadvanage srucure by he logc of compeency ndcaor sysem compeency evaluaon mehod based on dsadvanage srucure opmzaon model nverse opmzaon converng soluon. The man conrbuon of he arcle s as follows: frsly, we propose a mehod whch can nroduce psychology and behavor feaures no opmzaon model; secondly, we propose a new mehod whch can solve he problem whose deal soluon s known, we ry o make he deal soluon he opmmal soluon wh he mehod of adjus he opmzaon parameers, and wh consderaon of he sably of he orgnal sysem(descrbed by forward opmzaon model), we clam ha he adjusmen s as small as possble. Thrdly, hs mehod solves he problem of he forward opmzaon parameers are unknown or changeable, bu we can gve a esmaon value accordng o experence, wha we need o do s o deermne he parameer value. I promoes he combnng of psychology, behavor and operaon research, s good for process ndusres o develop n a safey and effcency way. Acknowledgemens The research work was suppored by Youh Projec of Naonal Naural Scence Foundaon (740023), Youh Projec of Humanes and Socal Scences Fund of Educaon Mnsry (4YJC6309), Chna Posdocoral Scence Foundaon(207M6083),Laonng Provnce Socal Scence Assocaon (207lslkyb-049) and Dalan Cy Socal Scence Assocaon (206dlskyb03). References. Na-Wen L I, Zh-Jang P Z. Sudy on Pos Safey Compeency Model of Specal Operaon Personnel n Coal Enerprse[J]. Chna Safey Scence Journal, 2008, 8(): L T, L M L, Yang X G, e al. Human Resource Demand and Supply Model for Naonal Research Insuons of Chna[J]. Managemen Revew, 20, 23(4): Ma X Y. Applcaon of Assgnmen Model n PE Human Resources Allocaon[J]. Energy Proceda, 202, 6(6): Chen T H, Ln Y, Ten K W. Agen-based negoaon mechansm for mul-projec human resource allocaon[j]. Journal of Indusral & Producon Engneerng, 203, 30(8): Yu M, Gong J, Luo X G, e al. Saffng Model for Call Cener wh Cusomer Paence Varaon[J]. Journal of Sysems Engneerng, 203, 28(5): Zhang L L, Zhao X N, Zang Y Y. Four-n-one Human Capal Machng Mehod Based on Advanage Srucure Idenfcaon[J]. Sysems Engneerng-Theory & Pracce, 203, 33(8): Avso K B, Mayol A P, Promenlla M A B, e al. Allocang human resources n organzaons operang under crss condons: A fuzzy npu-oupu opmzaon modelng framework[j]. Resources Conservaon & Recyclng, 206.

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