Optimal labour allocation for energy, economic and environmental sustainability in the United Arab Emirates: A goal programming approach

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1 Avalable onlne at Energy Proceda 00 (2015) The 7 th Internatonal Conference on Appled Energy ICAE2015 Optmal labour allocaton for energy, economc and envronmental sustanablty n the Unted Arab Emrates: A goal programmng approach Abstract Raja Jayaraman a, *, Davde La Torre b, c, Tufal Malk b, Yanthe E. Pearson b a Department of Industral & Systems Engneerng, Khalfa Unversty, Abu Dhab, UAE b Department of Appled Mathematcs and Scences, Khalfa Unversty, Abu Dhab, UAE c Department of Economcs, Management and Quanttatve Methods, Unversty of Mlan, Mlan 20122, Italy Sustanable development s an mportant and strategc prorty for global natons whch requres smultaneously satsfyng multple conflctng objectves nvolvng socal, economc, energy, and envronmental constrants. Mult-crtera decson analyss usng a goal programmng approach, s a popular and wdely used technque to study real world problems nvolvng conflctng objectves due to modellng smplcty and elegance. In ths paper we propose a goal programmng model that ntegrates effcent allocaton of labour resources to acheve sustanablty objectves relatng to economc, energy and envronmental goals of the Unted Arab Emrates by the year The proposed soluton provdes mathematcal and economc justfcaton wth crtcal nsghts to prortze areas for strategc plannng and resource allocaton to develop and mplement amenable strateges for sustanablty The Authors. Publshed by Elsever Ltd. Selecton and/or peer-revew under responsblty of ICAE Keywords: Sustanablty, Goal Programmng Model, Energy Consumpton, Envronment 1. Introducton An agenda for sustanablty requres focused efforts to mnmze consumpton of natural resources, an ncreased dependence on renewable energy, sustaned efforts to reduce GHG emssons and commtted leadershp. The nteracton between energy consumpton, economc growth and ts effects on * Correspondng author. Tel.: ; fax: E-mal address: raja.jayaraman@kustar.ac.ae

2 2 Jayaraman, R. et al./ Energy Proceda 00 (2015) envronmental degradaton requres sutable trade-offs to develop amenable polces. The changng demographcs and economc growth are contrbutors to a steep ncrease n Green House Gas (GHG) emssons and consumpton of natural resources. Despte nternatonal efforts to reduce emssons, GHG emssons are growng and accumulatng at an acceleratng pace due to extensve use of fossl fuel based energy sources [1]. To address the sustanablty challenge multple conflctng objectves on economc development, energy consumpton, populaton, socal and envronment should be smultaneously consdered. The objectve of ths paper s to address some of the crtera towards achevng sustanablty goals of the Unted Arab Emrates (UAE) by the year In recent decades the UAE has wtnessed remarkable economc growth makng t the 7 th largest GDP per capta, and the 10 th largest ol producng country n the world. The UAE has hstorcally depended on hydrocarbon based revenue snce ndependence n 1971 [2]. To support the rapdly growng economy, ncreased populaton and energy needs, the UAE has taken several mportant ntatves towards economc dversfcaton. In recent years t has heavly nvested n non-ol sectors such as technology, nfrastructure, educaton, fnance, trade, and manufacturng, to help support long-term sustanablty, whch provdes mmunty aganst ol prce fluctuatons. Terdman [3] presents a dscusson on the green economy and sustanable development ntatves of the UAE. The UAE Vson 2021 [4] specfcally addresses the strong need to develop and promote renewable energy sources advocatng lower GHG emssons. The electrcty demand n the UAE has grown from GWh n 2000 to GWh n 2009, to GWh n 2010, wth an average annual ncrease rate of about 8.8% durng the last decade [5]. Between the years 2006 and 2011, the annual ncrease n electrcty demand (10.8%) has closely followed the trend n annual populaton growth of 11% durng the same perod [5]. The populaton growth of the UAE has been phenomenal-from 1 mllon n 1980, to 8.4 mllon n 2010 and mllon n 2013 [6]. The UAE populaton consttutes a dverse mx of natonaltes and cultures wth over 80% expats or non - UAE natonals, wth a market heavly dependent on foregn labor for future development and growth. More generally, when comparng the average annual percent change n populaton, the UAE s placed at 10 th among 230 countres wth a growth rate of 3.06% [7]. A populaton growth of ths proporton can be drectly lnked to an ncreased electrcty consumpton and over consumpton of other natural resources. Conservatve estmates predct that the per capta electrcty consumpton n the Gulf Cooperaton Countres (GCC) countres s lkely to ncrease at an annual rate of 2.5% [8]. Electrcty generaton n the UAE s manly through natural gas; ths leads to severe envronmental concerns, ncludng ncreased producton of CO 2, SO 2, and other GHG s and partculate matter. Over 97.5% of power generaton across the country comes from natural gas-powered plants [12]. Due to the lmted ground water potental, water requrements for the growng populaton are predomnantly met by desalnaton. Water desalnaton plants are a sgnfcant source of energy consumpton, GHG emssons and ar polluton [9]. The UAE s CO 2 emssons have ncreased from 6080 Gg n 1990 to Gg n 2008 [10]. Of these emssons, the largest contrbutons were due to power generaton [10]. It s nterestng to note that the, Mddle East and North Afrca (MENA) regon s regarded as the second most polluted regon n the world (followng South Asa), whch produces the hghest CO 2 levels per dollar of output [11]. Populaton growth and energy consumpton are obvous contrbutng factors to GHG emssons. In 2000, the UAE s total GHG emssons were Gg of CO 2 equvalent, and the current fgures show a 64% ncrease n total GHG emssons snce In order to meet the long-term emsson reducton goals, the top prorty s to reduce the need for fossl fuels by nvestng n clean technologes for energy producton. Usage of renewables would present multple benefts to the UAE, most mportantly to reduce the dependence on hydrocarbons. In ths paper we present a goal programmng (GP) approach to study the nteractons between goals related to electrcty consumpton (G1), GHG emssons (G2), GDP growth (G3), and number of employees (G4) from varous economc sectors and ther contrbuton to the future economc

3 Jayaraman, R. et al./ Energy Proceda 00 (2015) sustanablty goals by the year GP models provde an deal framework that a decson maker can use to prortze resource allocaton n the presence of multple competng objectves. GP models are amed at meetng the quantfed goals as closely as possble, where the Decson Maker (DM) tres to mnmze the dstances between the goals and the actual values of the crtera or objectve functons n the decson procedure. A goal s a numercal level (the target level) the DM desres to acheve, relatve to each crteron. The numercal lmt can be over-acheved, under-acheved or completely acheved. The paper s organzed as follows, In the next secton we dscuss data preparaton and analyss. Secton 3 descrbes the goal programmng model and soluton, n secton 4 we present bref conclusons and future extensons of the model. 2. Data Preparaton and Analyss In ths paper we have used the followng 8 sectors: () agrculture, () crude ol, natural gas and mnng, () manufacturng and electrcty, (v) constructon and real estate, (v) trade and transport, (v) restaurant and hotel, (v) bankng and fnancal corporatons and (v) government, socal and personal servces. The goal related to (G1) electrcty consumpton s projected to GWh n 2030 at 8% growth, (G2) GHG emssons are projected at Gg of CO2 equvalent at 2% growth, (G3) GDP growth was projected at 7% to reach 2725 Bllon AED by the year Goal related to total number of labour n each sector s (G4). The projected populaton growth n the UAE s estmated to be mllon for the year 2030 [6]. Sectoral data for varous economc, envronmental, labour ndcators for the UAE were obtaned from dverse sources. The GDP contrbuton and number of employees for the dentfed sectors were obtaned from the Mnstry of Economy s Annual Economc Report, 2012[13]. The sectoral data for electrcty consumpton were obtaned from the Internatonal Energy Agency wth reference to the year 2011[14]. The collected data dd not provde sector specfc estmates for electrcty consumpton; so we used the percentle contrbuton of GDP relatve to each sector for dsaggregaton. GHG emsson data for the year 2005 (the most updated entry) were obtaned from the Thrd Natonal Communcaton under the Unted Natons Framework Conventon on Clmate Change, 2013[15]. Table 1: Sectoral Indcators for Unted Arab Emrates Economy Decson Varable Sector GDP Per Capta (In Mllon AED) Electrcty Consumpton Per Capta (GWh) GHG Emssons Per Capta (Gg of CO 2) X 1 Agrculture X 2 Crude Ol, Natural Gas & Mnng X 3 Manufacturng & Electrcty X 4 Constructon & Real estate X 5 Trade & Transport X 6 Restaurant & Hotel X 7 Bankng & Fnancal Corporaton X 8 Government, Socal & Personal servces

4 4 Jayaraman, R. et al./ Energy Proceda 00 (2015) Goal Programmng Model The GP model s a well-known aggregatng methodology for solvng mult-objectve problems and decson-makng processes. GP models smultaneously take nto account several conflctng objectves. The soluton obtaned through the GP model represents the best compromse that can be made by the DM. The frst formulaton of the GP model was presented n 1955 by Charnes et al. [16], further expanded n Charnes and Cooper [17, 18], Lee [19] and Lee and Clayton [20]. GP models are wdely appled n several felds such as: accountng and fnancal aspect of stock management, marketng, qualty control, human resources, producton and operatons management [22-27]. Accordng to Aoun and Kettan [21] the GP s supported by a well-establshed network of researchers and practtoners. If f ( x ) s the vector of crtera to be optmzed, g s the vector of the goals and D s the feasble set, the standard mathematcal formulaton of the GP model [28] s as follows: Where δ, p Mn Z δ + δ = =1 + Subject to (1) + ƒ x + δ δ = g = p δ ( ), 1... ; x D; + δ, δ 0, = 1... p + are, respectvely, the negatve and the postve devatons wth respect to the aspraton levels (goals) g, =1 p. An alternatve defnton of the GP model whch wll be useful n the sequel s the Weghted Goal Programmng (WGP) that can formulated as follows: where w, p Mn Z = w + δ + w δ =1 + Subject to (2) w + ( x) δ δ g, 1... p; ƒ + = = x D; 3.1. Model Formulaton + δ, δ 0, = 1... p + are the weghts assocated wth the negatve and the postve devatons. Usng the data presented n Table 1, and the goals for the four crtera set at g 1= , g 2=286980, g 3=284739, and g 4= The WGP model descrbed n equaton (2) wth weghts w equal to 0.25 can be formulated. The GP model nvolves the followng crtera: Gross GDP f 1(X 1, X 2, X 3, X 4, X 5, X 6, X 7, X 8) := *X *X *X *X *X *X *X *X 8 Electrcty consumpton

5 Jayaraman, R. et al./ Energy Proceda 00 (2015) f 2(X 1, X 2, X 3, X 4, X 5, X 6, X 7, X 8) := *X *X *X *X *X *X *X *X 8 GHG emsson f 3(X 1, X 2, X 3, X 4, X 5, X 6, X 7, X 8) := *X *X *X *X *X *X *X *X 8 Total labor force f 4(X 1, X 2, X 3, X 4, X 5, X 6, X 7, X 8) := X 1+X 2+X 3+X 4+X 5+X 6+X 7+X 8 Mn Z = 0.25*(D 11+D 12) +0.25*(D 21+D 22) +0.25*(D 31+D 32) +0.25*(D 41+D 42); Subject to: *X *X *X *X *X *X *X *X 8+D 11-D 12= , *X *X *X *X *X *X *X *X 8+D 21 -D 22=286980, *X *X *X *X *X *X *X *X 8+D 31-D 32=284739, X 1+X 2+X 3+X 4+X 5+X 6+X 7+X 8+D 41-D 42= , () () () (v) X , X , X , X , X , X , X , X , X 1, X 2, X 3, X 4, X 5, X 6, X 7, X 8 are nteger (v) (v) (v) (v) (x) (x) (x) (x) (x) D 0 (xv) j Some comments on the above formulaton The objectve functon ncludes the weghted summatons of all postve and negatve devatons of each crteron wth respect to ts correspondng goal. Constrants () to (v) show a lnear relatonshp among the achevement level of each crteron, the correspondng goals and the devatons. The smaller the devatons, the smaller are the dfferences between the achevement levels and the goals. The remanng constrants, (v) to (x) mpose that the optmal soluton has to preserve at least the current number of jobs, whch s a realstc assumpton.

6 6 Jayaraman, R. et al./ Energy Proceda 00 (2015) Soluton The soluton of the model obtaned usng LINGO s presented n Table 2. The output shows the presence of a bg nonzero devaton n D 22. Ths can be nterpreted as follows, to smultaneously satsfy all the four crtera n the model requres a huge amount of energy demand that cannot be satsfed usng fossl fuel sources alone. An ncrease of crude ol producton, n fact, would ncrement GHG emssons and ths, as a consequence, wll affect the values of other devatons nvolved n the GP model. Therefore to acheve sustanablty goals and avod any ncrement n GHG emssons, the only reasonable alternatve s to alter the energy consumpton by ncludng green (alternatve) energy sources to satsfy the growng energy needs. 4. Conclusons Table 2: LINGO output of the optmal soluton Devatons Value Reduced Cost Varable Value Reduced Cost D X D E X D X D X D X D X D X D X In ths paper we have developed a WGP model that ntegrates optmal labor allocaton to smultaneously satsfy the prospectve targets of economc development, energy consumpton, workforce, and GHG emsson reducton by the year 2030 for the UAE. The model offers a mathematcal justfcaton for necessary changes to the current energy portfolo, and the mportance of usng clean energy sources to satsfy the consumpton patterns. In the next ten years, the UAE wll see the ntroducton of nuclear power plants and the hghly antcpated move towards renewable technologes, namely solar power and wnd whch holds huge potental for sustanablty goals. The model can be expanded n several ways, the authors are currently workng on the stochastc extenson of the model, where the goals, achevement functons and coeffcents may not be known wth certanty. Acknowledgements The authors are grateful to the support and fundng from Khalfa Unversty Internal Research Fund (KUIRF) - Grant number to conduct ths research. References [1] Energy & Clmate Change Polcy and Progress- Unted Arab Emrates. Accessed onlne: [2] U.S. Energy Informaton Admnstraton (EIA). URL: [3] Terdman, M. (2012). Green Economy n Acton: Artcles and Excerpts that llustrate green economy and sustanable development, Unted Natons Development Programme (UNDP), (Accessed on 12 January, 2014) [4] UAE Vson Retreved onlne URL:

7 Jayaraman, R. et al./ Energy Proceda 00 (2015) [5] Mokr, A., Aal Al, M., & Emzane, M. (2013). Solar energy n the Unted Arab Emrates: A revew. Renewable and Sustanable Energy Revews, 28, [6] UN World Populaton Prospects: The 2012 Revson. URL: [7] CIA world fact book ( [8] Delotte, Energy on demand: The future of GCC energy effcency, Mddle east energy and resources. [9] DeFelce, N. B., & Gbson, J. M. (2013). Effect of domestc water use on ar pollutant emssons n Abu Dhab, Unted Arab Emrates. Internatonal Journal of Energy and Envronmental Engneerng, 4(1), 33. [10] Kazm, A. M. (2007). Assessments of prmary energy consumpton and ts envronmental consequences n the Unted Arab Emrates. Renewable and Sustanable Energy Revews, 11(3), [11] Omr, A. (2013). CO2, emssons, energy consumpton and economc growth nexus n MENA countres: Evdence from smultaneous equatons models. Energy Economcs, 40, [12] Global busness reports, Power UAE, Shftng Sands, Aprl [13] UAE Mnstry of Economy-Annual Economc Report, Retreved onlne: [14] Internatonal Energy Agency, (2011). [15] Unted Natons Framework Conventon on Clmate Change. URL: natcom/tems/2979.php [16] Charnes, A., Cooper, W.W. and Ferguson, R. (1955), Optmal estmaton of executve compensaton by lnear programmng, Management Scence, 1, [17] Charnes, A. and Cooper, W.W. (1959), Chance-constraned programmng, Management Scence, 6, [18] Charnes, A. and Cooper, W.W. (1968), Determnstc equvalents for optmsng and satsfyng under chance constrants, Operatons Research, 11 (1968), [19] Lee, S.M. (1973), Goal programmng for decson analyss of multple objectves, Sloan Management Revew, 14 (1973), [20] Lee, S.M. and Clayton, S.R. (1972), A goal programmng model for academc resource allocaton, Management Scence, 18 (8), B395-B408. [21] Aoun, B. and Kettan, O. (2001), Goal programmng model: a glorous hstory and a promsng future, European Journal of Operatons Research, 133, 2, 1-7. [22] Aoun, B., Kettan, O. and Martel, J-M. (1997), Estmaton through mprecse goal programmng model, n: R. Caballero, F. Ruz and R.E. Steuer (eds.), Advances n mult-objectve and goal programmng, Lecture Notes n Economcs and Mathematcal Systems, 455, Sprnger, [23] Aoun, B., Colapnto, C., La Torre, D. (2012a), A cardnalty constraned goal programmng model wth satsfacton functon for venture captal nvestment decson makng, Annals of Operatons Research, DOI: /s [24] Aoun, B., Colapnto, C., La Torre, D. (2012b), A scenaro-based stochastc goal programmng model wth satsfacton functon: applcaton to meda management and strategy, Internatonal Journal of Multcrtera Decson Analyss, 2, 4, [25] Aoun, B., Ben Abdelazz, F., La Torre, D. (2012c), The Stochastc Goal Programmng Model: Theory and Applcatons, Journal of Multcrtera Decson Analyss, 19, 5-6, [26] Aoun, B., Colapnto, C., La Torre, D. (2010), Solvng Stochastc Mult-Objectve Programmng n Mult-Attrbute Portfolo Selecton through the Goal Programmng Model, Journal of Fnancal Decson Makng, 6, 2, [27] Aoun, B., La Torre, D. (2010), A generalzed stochastc goal programmng model, Appled Mathematcs and Computaton, 215, [28] Charnes, A. and Cooper, W.W. (1952), Chance constrants and normal devates, Journal of the Amercan Statstcal Assocaton, 57, Bography Raja Jayaraman s an Assstant Professor of Industral & Systems Engneerng at Khalfa Unversty, UAE. He receved hs Ph.D. n Industral Engneerng from Texas Tech Unversty, USA, a Master of Scence n Industral Engneerng from New Mexco State Unversty, USA, Masters and Bachelor degree n Mathematcs from Inda. Hs research nterests ncludes appled operatons research and optmzaton methods appled to qualty control, supply chans, healthcare and envronmental sustanablty.

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