How to use multiplication of variable inside gp.max_() ?

Answered

Md Yeakub Hassan

October 12, 2020 16:21

x is a continuous varibale, and a[] is an array of decision variables. I want to add the following

model.addConstr(x == gp.max_(a[0]*1, a[1]*3, a[2]*4))

But I am getting error. How to solve this?

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Comments

4 comments

Official comment
Simranjit Kaur

Gurobi Staff

June 23, 2025 03:06 Edited
This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum. Or why not try our AI Gurobot?.
Silke Horn

Gurobi Staff

October 13, 2020 09:38
The max_ function only takes a list of decision variables (or constants). You will have to define some auxiliary variables (say aux[1] and aux[2]) and add constraints as follows:
```
model.addConstr(aux[1] == a[1]*3)
model.addConstr(aux[2] == a[2]*4)
```
Then you can add the max constraint using the auxiliary variables:
```
model.addConstr(x == gp.max_(a[0], aux[1], aux[2]))
```
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Alexia Payan

May 21, 2021 22:21
Hello Silke,

I have a question regarding the use of the max_ function. I noticed that using it slows down the optimization somewhat. Is this because it is technically not a linear constraint? Have you ever observed a similar behavior?
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Alison Cozad

Gurobi Staff

June 14, 2021 14:45
Yes, adding the max_() constraints may make your model harder to solve. Depending on how \(x\) is used in your model, the max_() general constraint helper function will add either constraints or constraints and variables to your model. Please check out Part 2 of this Modeling presentation from when the general constraint helper functions were first introduced to get a feel for how this is done.
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