set MAT /m1*m5/;
* materials
set MATF(MAT) /m1,m2,m3,m5/;
* materials
set ACT /a1*a7/;
* activities

Table io[MAT,ACT]
           a1   a2  a3   a4   a5  a6  a7
 m1         1   -1   1   -1   -1  -1   1
 m2        -1    1  -1    1    1  -1   1
 m3         1   -1   1   -1   -1   1   1
 m4        -1    1  -1    1    1   1  -1
 m5         1   -1   1   -1   -1   1  -1 ;

* input-output coefficients

Parameter cost[ACT] /a1  2 , a2  1 , a3  2 , a4  1 , a5  1 , a6  2 , a7  1 /;
Parameter act_min[ACT] /a1  0 , a2  0 , a3  0 , a4  0 , a5  0 , a6  0 , a7  0 /;
Parameter act_max[ACT] /a1 20 , a2 25 , a3 25 , a4 25 , a5 25 , a6 25 , a7 25 /;

Parameter revenue[MAT]  /m1  2 , m2  1 , m3  2 , m5  1  /;
Parameter sell_min[MAT] /m1  0 , m2  0 , m3  0 , m5  0  /;
Parameter sell_max[MAT] /m1 35 , m2 43 , m3 42 , m5 35  /;


Variable X(act) ,sell(MAT) , Net_Profit ;
Equation Eq_Balance_1(MAT) , Eq_Balance_2(MAT) , Def_obj ;

Eq_Balance_1(MAT)$MATF(MAT)..
                      sum{ACT, io[MAT,ACT] * X[ACT]} =e= sell[MAT];
Eq_Balance_2(MAT)$(not MATF(MAT))..
                      sum{ACT, io[MAT,ACT] * X[ACT]} =e= 0;

Def_obj.. Net_Profit =e= sum{MAT$MATF(MAT), revenue[MAT] * sell[MAT]}-
                         sum{ACT, cost[ACT] * X[ACT] };

X.lo(ACT) = act_min(ACT) ;
X.up(ACT) = act_max(ACT) ;

sell.lo(MAT)$MATF(MAT) = sell_min(MAT) ;
sell.up(MAT)$MATF(MAT) = sell_max(MAT) ;

* AMPL solution
*sell.fx('m1') = 0;
*sell.fx('m2') = 0;
*sell.fx('m3') = 42;
*sell.fx('m4') = 0;
*X.fx('a1') = 0;
*X.fx('a2') = 0;
*X.fx('a3') = 0;
*X.fx('a4') = 21;
*X.fx('a5') = 21;

Model iocol2 /all/;
Solve iocol2 using nlp maximazing Net_Profit ;
Display Net_Profit.l ;