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yemcem.gms : Yemen Cement Model


A simple model of the cement sector for the Yemen Arab Republic
can be used to explore expansion plans under various assumptions
about domestic and world markets and cost structures.

Reference:
Large Model of Type: MIP
$Title Y E M E N Cement model (YEMCEM,SEQ=51) $Stitle Set definitions $Ontext A simple model of the cement sector for the Yemen Arab Republic can be used to explore expansion plans under various assumptions about domestic and world markets and cost structures. World Bank, Yemen Arab Republic - Manufacturing Industry: Performance, Policies and Prospectives. Tech. rep., The World Bank, 1982. $Offtext Sets i plants / amran, baijil, mafrak / j markets / sanaa, hodeideh, taizz, ibb, dhamar / m productive units / dry-kiln dry process kiln and ancillaries wet-kiln wet process kiln and ancillaries mills clinker-gypsum mills storage and packing / ms(m) productive units with economies of scale mp(m) productive units without economies of scale p process / dry dry process clinker production wet wet process clinker production grind clinker grinding / ca all commodities / limestone tons clay tons gypsum tons fuel 1000*liter petrol 1000*liter explosives kg grindparts kg refractory kg bags bag clinker tons cement tons / c(ca) commodities for material balance constraints / cement, clinker, fuel / cf(c) final products / cement / ci(c) imported intermediate products / clinker, fuel / cr(ca) local materials / limestone, clay, gypsum, petrol, explosives, grindparts, refractory, bags / t time periods / 1983-85, 1986-88, 1989-91, 1992-94 / te(t) expansion periods / 1986-88, 1989-91, 1992-94 / s kiln sizes / small, medium, large / Alias (te,tp) $Stitle parameters and data modifications Parameters pd(cr) domestic prices (yr per unit) / limestone 5.0 , clay 2.0 gypsum 24.6 , petrol 1175.0 explosives 4.0 , grindparts 3.328 refractory 4.0 , bags 1.31 / pv(ca) import prices (yr per ton) pe(ca) export prices (yr per ton) ebu(t) upper bound on exports (1000 tpy) vbu(t) upper bound on imports (1000 tpy) vibu(t) bound on klinker import(1000 tpy) ; pv("cement ") = 280 ; pv("clinker") = .8*pv("cement") ; pv("fuel ") = 600 ; pe(c) = .75*pv(c) ; ebu(t) = 1000 ; vbu(t) = 3000 ; vibu(t) = na; Display pd, pv, pe ; Table a(ca,p) input-output coefficients dry wet grind limestone -1.3 -1.3 clay -.3 -.3 gypsum -.04 petrol -.00147 -.00147 explosives -.192 -.192 grindparts -.385 refractory -.152 -.152 bags -20.0 fuel -.1127 -.1465 clinker .96 .96 -.96 cement 1.0 Table b(m,p) capacity utilization dry wet grind dry-kiln 1.0 wet-kiln 1.0 mills 1.0 Table k(m,i) capacities as of 1982 (1000 tpy) amran baijil mafrak dry-kiln 500.0 wet-kiln 320.0 mills 500.0 320.0 $Eject Table inv(m,*) capital investment data * cost millions yr (1978) * size 1000 tpy * scale scale factor - cost = constant*size**scale cost size scale dry-kiln 526.296 500.0 .53 wet-kiln 447.352 500.0 .56 mills 105.259 500.0 1.00 Parameters site(i) site factor / amran 1.2, baijil 1.15, mafrak 1.05 / size(s) kiln size (1000 tpy) / small 500, medium 750, large 1000 / klim(i) limit of total kiln capacity (1000 tpy) ts(t,t) time summation matrix midyear(t) delta(t) discount factor rc(p) recurrent cost (yr per process unit) fc(m) fixed cost (yr per ton) / dry-kiln 55.8, wet-kiln 60 / Scalars sigma capital recovery factor zeta life of productive units (years) rho discount rate ; ms(m)$(inv(m,"scale") ne 1) = yes; mp(m) = not ms(m) ; inv(ms,s) = inv(ms,"cost")*(size(s)/inv(ms,"size"))**inv(ms,"scale"); inv(mp,"prop") = inv(mp,"cost")/inv(mp,"size"); klim(i) = 2000 ; midyear(t) = 1981 + 3*ord(t) ; ts(te,tp)$(ord(te) ge ord(tp)) = 1; zeta = 30; rho = .1; sigma = rho/(1-(1+rho)**(-zeta)); delta(t) = (1+rho)**(1982-midyear(t)); rc(p) = - sum(cr, a(cr,p)*pd(cr)); Display ms, mp, midyear, ts, sigma, delta, inv, rc; $Eject Set ds demand scenarios (base year demand and growth rates) / bg-700-06, bg-700-11, bg-900-06, bg-900-11 / Parameters dt(ds,t) total demand for cement (1000 tpy) d(j,t,cf) regional demand for cement (1000 tpy) dd(j) demand distribution / sanaa 28, hodeideh 27, taizz 20, ibb 12.5, dhamar 12.5 /; dt("bg-700-06",t) = 700*1.06**(midyear(t)-1980); dt("bg-700-11",t) = 700*1.11**(midyear(t)-1980); dt("bg-900-06",t) = 900*1.06**(midyear(t)-1980); dt("bg-900-11",t) = 900*1.11**(midyear(t)-1980); d(j,t,"cement") = na; Display dd,dt; Table rd(*,*) road distances from plants to markets (km) sanaa taizz hodeideh dhamar ibb port amran 48 304 279 146 209 279 baijil 171 294 60 270 332 60 mafrak 319 63 213 220 157 213 port 231 276 5 329 371 Table f(*,*) cost increase factors for motor transport sanaa hodeideh taizz dhamar ibb port amran 1.15 1.14 1.16 1.14 1.16 1.14 baijil 1.14 1.11 1.13 1.13 1.14 1.11 mafrak 1.16 1.11 1.17 1.17 1.16 1.11 port 1.14 1.0 1.14 1.16 1.15 1.0 Parameters muf(i,j) cement transport cost (yr per ton) muv(j) import transport cost (yr per ton) mui(ci,i) import intermediate transport cost (yr per ton) mue(i) export transport cost (yr per ton) ; muf(i,j) = 30 + .47*f(i,j)*rd(i,j); muv(j) = 30 + .47*f("port",j)*rd("port",j); mue(i) = 30 + .47*f(i,"port")*rd(i,"port"); mui(ci,i)= 30 + .35*f(i,"port")*rd(i,"port"); mui("fuel ",i) = 1.5*mui("clinker",i); Display muf, muv, mue, mui; $Stitle breakeven analysis Parameter tpn(i,*) transport protection (yr per ton) vc variable cost of cement production (yr per ton) fxc(i,s) fixed cost of cement production (yr per ton) ac(i,s) average cost of cement production (yr per ton) mbe(i,*) marginal breakeven price (yr per ton) abe(i,*) average breakeven price (yr per ton) ; tpn(i,"v-inputs") = -a("fuel","dry")*mui("fuel",i); tpn(i,"plant-gate") = mue(i) - tpn(i,"v-inputs") ; tpn(i,j) = muv(j) - (tpn(i,"v-inputs")+muf(i,j)); vc = 1.025*(-a("fuel","dry")*pv("fuel") + rc("dry") + rc("grind")); fxc(i,s) = 1000*sigma*site(i)*(inv("dry-kiln",s)/size(s) + inv("mills","prop")) + 1.025*(fc("dry-kiln")+fc("mills")); ac(i,s) = vc + fxc(i,s); mbe(i,j) = vc - tpn(i,j) ; mbe(i,"plant-gate") = vc - tpn(i,"plant-gate") ; abe(i,j) = ac(i,"small") - tpn(i,j) ; abe(i,"plant-gate") = ac(i,"small") - tpn(i,"plant-gate") ; Display tpn, vc, fxc, ac, mbe, abe; $Stitle model specification Variables z(p,i,t) process level (1000 units per year) x(c,i,j,t) shipment of cement (1000 tpy) v(cf,j,t) imports of cement (1000 tpy) vi(c,i,t) imports of intermediates (1000 units per year) e(c,i,t) export of cement (1000 tpy) h(m,i,te) capacity expansion (1000 tpy) y(m,i,s,te) binary variable phi total discounted cost phikap(t) capital investment charge (mill yr per year) phipsi(t) recurrent cost (mill yr per year) philam(t) transport cost (mill yr per year) phipi (t) import cost (mill yr per year) phieps(t) export revenue (mill yr per year) phiw (t) working capital charge (mill yr per year) ; Positive Variables z, x, v, vi, e, h; Binary Variable y; Equations mb(c,i,t) material balances (1000 units per year) cc(m,i,t) capacity constraints (1000 tpy) id(m,i,te) investment definition ich(m,i,te) investment choice limit(i) capacity limit(i) (1000 tpy) mr(cf,j,t) market requirement (1000 tpy) eb(t) export limit (1000 tpy) vb(t) import limit: cement (1000 tpy) vib(t) import limit: clinker (1000 tpy) obj total discounted costs apsi(t) recurrent cost acct (mill yr per year) akap(t) investment cost acct (mill yr per year) alam(t) transport cost acct (mill yr per year) api (t) import cost acct (mill yr per year) aeps(t) export revenue acct (mill yr per year) aw (t) working capital acct (mill yr per year) ; mb(c,i,t).. sum(p, a(c,p)*z(p,i,t)) + vi(c,i,t)$ci(c) =g= (sum(j, x(c,i,j,t)) + e(c,i,t))$cf(c) ; cc(m,i,t).. sum(p, b(m,p)*z(p,i,t)) =l= k(m,i) + sum(tp$ts(t,tp), h(m,i,tp)) ; id(ms,i,te).. h(ms,i,te) =e= sum(s, size(s)*y(ms,i,s,te)); ich(ms,i,te).. sum(s, y(ms,i,s,te)) =l= 1.0 ; limit(i).. sum(ms, k(ms,i) + sum(te, h(ms,i,te))) =l= klim(i) ; mr(cf,j,t).. sum(i, x(cf,i,j,t)) + v(cf,j,t) =g= d(j,t,cf) ; eb(t).. sum((cf,i), e(cf,i,t)) =l= ebu(t) ; vb(t).. sum((cf,j), v(cf,j,t)) =l= vbu(t) ; vib(t).. sum(i, vi("clinker",i,t)) =l= vibu(t) ; obj.. phi =e= sum(t, delta(t)*( phikap(t) + phipsi(t) + philam(t) + phipi(t) + phiw(t) - phieps(t) )) ; apsi(t).. phipsi(t) =e= .001*( sum((p,i), rc(p)*z(p,i,t)) + sum((i,m), fc(m)*( k(m,i) + sum(tp$ts(t,tp), h(m,i,tp))))) ; akap(t).. phikap(t) =e= sigma*sum(tp$ts(t,tp), sum((ms,i,s), site(i)*inv(ms,s)*y(ms,i,s,tp)) + sum((mp,i), site(i)*inv(mp,"prop")*h(mp,i,tp)) ) ; alam(t).. philam(t) =e= .001*( sum(cf, sum((i,j), muf(i,j)*x(cf,i,j,t)) + sum(j, muv(j)*v(cf,j,t)) + sum(i, mue(i)*e(cf,i,t)) ) + sum((ci,i), mui(ci,i)*vi(ci,i,t)) ) ; aeps(t).. phieps(t) =e= .001*sum((cf,i), e(cf,i,t)) ; api(t).. phipi(t) =e= .001*( sum((cf,j), pv(cf)*v(cf,j,t)) + sum((ci,i), pv(ci)*vi(ci,i,t)) ) ; aw(t).. phiw(t) =e= .25*.1*(phipsi(t) + phipi(t)); Model yemen yemen cement model / all / ; * definition of scenario number 16: d(j,t,"cement") = dt("bg-900-11",t)*dd(j)/100; vibu(t) = 0; y.fx("dry-kiln","mafrak","small","1986-88") = 1; Solve yemen minimizing phi using mip; Display z.l, h.l ; Parameters xx(i,*,t) cement shipments (1000 tpy) kh(*,t) total kiln capacity (1000 tpy) mcc(i,t,m) shadow price on capacity - undiscounted mmr(j,t) shadow price on requirements - undiscounted ; xx(i,j,t) = x.l("cement",i,j,t); xx(i,"**total**",t) = sum(j, xx(i,j,t)); kh(i,t) = sum(ms, k(ms,i) + sum(tp$ts(t,tp), h.l(ms,i,tp))); kh("total",t) = sum(i, kh(i,t)); mcc(i,t,m) = cc.m(m,i,t)/delta(t)*1000 ; mmr(j,t) = mr.m("cement",j,t)/delta(t)*1000 ; Display xx, kh, mcc, mmr ;