mathematical optimization - Using min/max *within* an Integer Linear Program

Question

I'm trying to set up a linear program in which the objective function adds extra weight to the max out of the decision variables multiplied by their respective coefficients.

With this in mind, is there a way to use min or max operators within the objective function of a linear program?

Example:

Minimize
    (c1 * x1) + (c2 * x2) + (c3 * x3) + (c4 * max(c1*x1, c2*x2, c3*x3)) 
subject to
    #some arbitrary integer constraints:
    x1 >= ...
    x1 + 2*x2 <= ... 
    x3 >= ...
    x1 + x3 == ...

Note that (c4 * max(c1*x1, c2*x2, c3*x3)) is the "extra weight" term that I'm concerned about. We let c4 denote the "extra weight" coefficient. Also, note that x1, x2, and x3 are integers in this particular example.

I think the above might be outside the scope of what linear programming offers. However, perhaps there's a way to hack/reformat this into a valid linear program?

If this problem is completely out of the scope of linear programming, perhaps someone can recommend an optimization paradigm that is more suitable to this type of problem? (Anything that allows me to avoid manually enumerating and checking all possible solutions would be helpful.)

Answer 1

Add in an auxiliary variable, say x4, with constraints:

x4 >= c1*x1
x4 >= c2*x2
x4 >= c3*x3  
Objective += c4*x4