Piecewise constraints in GAMS

Question

I'm trying to solve the network problem below in GAMS Cplex. I have a piecewise constraint that are depending on the node situations (whether a node is an origin (o) node, inbetween node, and destination (d) node). How do I write these piecewise contraints?

In the program below, I've write: eq1 represents node 1 as an origin node, eq2 eq3 eq4 represents node 2,3, and 4 as inbetween nodes, eq5 represents node 5 as a destination node.

Set

i   nodes /1,2,3,4,5/;

Alias(i,j);

Set
arc(i,j) arcs from node i to j 
/1 .2
 2 .1
 1 .3
 3 .1
 1 .4
 4 .1
 2 .3
 3 .2
 2 .5
 5 .2
 3 .5
 5 .3
 4 .5
 5 .4/;

Table c(i,j) population exposed from node i to node j
         1          2           3           4           5

1        0          105000      90000       65000       0

2        105000     0           100000      0           85000      

3        90000      100000      0           0           80000

4        65000      0           0           0           55000

5        0          85000       80000       55000       0
;

Table l(i,j) distance from node i to node j
         1          2           3           4           5

1        0          5           8           10          0

2        5          0           2           0           7      

3        8          2           0           0           11

4        10         0           0           0           8

5        0          7           11          8           0

Binary Variables
x(i,j)
y(i,j);
    
Positive Variables
    v(i,j)
    lambda(i,j);

Free Variables
    w(i) node i
    w(j) node j
    z optimization solution;
    
Scalar
    R very large number;

R = 10000000000000000;

Equations
    sol optimization solution
    eq1(i,j) constraint 1
    eq2(i,j) constraint 2
    eq3(i,j) constraint 3
    eq4(i,j) constraint 4
    eq5(i,j) constraint 5
    eq6(i,j) constraint 6
    eq7(i,j) constraint 7
    eq8(i,j) constraint 8
    eq9(i,j) constraint 9;
    
sol.. z =e= sum(arc(i,j),c(arc)*x(arc));
eq1(i,j).. x(1,2) - x(2,1) + x(1,3) - x(3,1) + x(1,4) - x(4,1) =e= 1;
eq2(i,j).. - x(1,2) + x(2,1) + x(2,3) - x(3,2) + x(2,5) - x(5,2) =e= 0;
eq3(i,j).. - x(1,3) + x(3,1) - x(2,3) + x(3,2) + x(3,5) - x(5,3) =e= 0;
eq4(i,j).. - x(1,4) + x(4,1) + x(4,5) - x(5,4) =e= 0;
eq5(i,j).. - x(2,5) + x(5,2) - x(3,5) + x(5,3) - x(4,5) + x(5,4) =e= -1;
eq6(i,j).. - y(i,j) + x(i,j) =l= 0;
eq7(i,j).. l(i,j) - w(i) + w(j) - v(i,j) + lambda(i,j) =e= 0;
eq8(i,j).. v(i,j) - R * (1 - x(i,j)) =l= 0;
eq9(i,j).. lambda(i,j) - R * (1 - (y(i,j) - x(i,j))) =l= 0;
Model contohTMB /all/;

Solve contohTMB using MIP Minimizing z;

Display "Solution values:"
Display
    x.l, z.l;

Answer 1

This can be done with $ ("such-that") conditions on the constraints. Or better: use a single parameter so that a single equation can be used for all cases (see: https://yetanothermathprogrammingconsultant.blogspot.com/2018/02/modeling-vs-programming-python-vs-gams.html for an example).

Your model can be improved a bit.

1. Use meaningful names.
2. Never use a big M constant of this size.
3. Use explanatory text on all symbols to explain what they mean. Something better than "constraint 3".

You may want to discuss this with your teacher.