Structural Optimization of Process Flowsheets minco LINDO GAMS short | 2 |----->+ | A | +-----+ | | B1 +-----+ C1 ---->| +----+------->| 1 |--------> | +-----+ | +-----+ +----->| 3 |----->+ A3 +-----+ B3 $Offtext $Eolcom ! Positive Variables a2 consumption of chemical a in process 2 a3 consumption of chemical a in process 3 b2 production capacity of chemical b in process 2 b3 production capacity of chemical b in process 3 bp amount of chemical b purchased in external market b1 consumption of chemical b in process 1 c1 production capacity of chemical c in process 1 ; Binary Variables y1 denotes potential existence of process 1 y2 denotes potential existence of process 2 y3 denotes potential existence of process 3 ; Variable pr total profit in million $ per year ; Equations inout1 input-output for process 1 inout2 input-output for process 2 inout3 input-output for process 3 mbalb mass balance for chemical b log1 logical constraint for process 1 log2 logical constraint for process 2 log3 logical constraint for process 3 obj profit objective function ; * the original constraint for inout2 is b2 = log(1+a2) * but this has been convexified to the form used below. * the same is true for inout3. so b2 and b3 are the * output variables from units 2 and 3 respectively inout1.. c1 =e= 0.9*b1 ; inout2.. exp(b2) - 1 =e= a2 ; inout3.. exp(b3/1.2) - 1 =e= a3 ; mbalb.. b1 =e= b2 + b3 + bp ; log1.. c1 =l= 2*y1 ; log2.. b2 =l= 4*y2 ; log3.. b3 =l= 5*y3 ; obj.. pr =e= 11*c1 ! sales revenue - 3.5*y1 - y2 - 1.5*y3 ! fixed investment cost - b2 - 1.2*b3 ! operating cost - 1.8*(a2+a3) - 7*bp ; ! purchases * demand constraint on chemical c based on market requirements c1.up = 1; Model process /all/ ; Solve process maximizing pr using minlp ; ]]> Structural optimization of process flowsheets with 8 equations, 11 variables (3 discrete), and 26 non-zeroes.