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2024 Jan 29
1
linear programming in R | limits to what it can do, or my mistake?
...create a coefficient matrix (typically, the LHS) since each line of said
matrix, which corresponds to the constraints, needs to be a function of
the unknowns in the objective function -- being, p1, p2, p3 and p4.
In Maple (for example), this is trivial:
???? cost:=35*p10+55*p12+50*p14+65*p16;
cnsts:={t10=640,t12=t10-p10+825,t14=t12-p12+580,t16=t14-p14+925,t16-p16=0,p10<=t10,p12<=t12,p14<=t14,p16<=t16,t10<=1000,t12<=1000,t14<=1000,t16<=1000};
? ?? Minimize(cost,cnsts,assume={nonnegative});
which yields (correctly):
p1=640, p2=405, p3=1000, p4=925
for minimized cost...
2024 Jan 30
1
linear programming in R | limits to what it can do, or my mistake?
...cally, the LHS) since each line of said
> matrix, which corresponds to the constraints, needs to be a function of
> the unknowns in the objective function -- being, p1, p2, p3 and p4.
>
> In Maple (for example), this is trivial:
>
> ???? cost:=35*p10+55*p12+50*p14+65*p16;
> cnsts:={t10=640,t12=t10-p10+825,t14=t12-p12+580,t16=t14-p14+925,t16-p16=0,p10<=t10,p12<=t12,p14<=t14,p16<=t16,t10<=1000,t12<=1000,t14<=1000,t16<=1000};
> ? ?? Minimize(cost,cnsts,assume={nonnegative});
>
> which yields (correctly):
>
> p1=640, p2=405, p3=1000, p...