5
votes
Accepted
Is it possible to merge two objective functions using the LpSolve package in R?
There are a variety of ways to deal with multiple objectives, so the answer is "it depends".
Probably the most common approach is to optimize a weighted sum or difference of the individual ...
- 29.6k
4
votes
How to model Max-Cut as ILP
To start with maxcut, you can start with the maxcut example in how to with OPL ?
...
- 3,517
4
votes
Accepted
How to model Max-Cut as ILP
Let $V$ and $E$ be the sets of vertices and edges respectively. Define a binary variable $x_v$ for each vertex $v\in V$ to be 1 if the vertex is on the "left" side of the cut and 0 if it is ...
- 29.6k
3
votes
Accepted
Modeling Multi-Agent Collision in Google CP-SAT Solver
Here is my proposal:
for each arc: (one vertical or horizontal segment of an path)
create a start variable
compute a min duration
create a end variable
create an variable interval with those 3 ...
- 1,724
3
votes
Google CP-SAT Infeasible ILP for Large Problem Area
With 256, I get the optimal solution quite fast.
With > 256, I get the following error:
...
- 1,724
2
votes
Multiprocessor Scheduling Problem: How to modify some constraints after variable changing?
The condition (*), that every job is assigned to exactly one machine, simply requires $$\sum_{i=k}^n z_{i,k} \ge 1 \quad \forall i=1,\dots,n.$$ That ensures that every job belongs to a cluster. It ...
- 29.6k
2
votes
Accepted
How to model this problem?
If it is desired to keep the new points somewhat close together rather than dispersed from each other, then I do not think the conditional $p$ dispersion problem is applicable. If we assume a discrete ...
- 29.6k
1
vote
Accepted
Google CP-SAT Infeasible ILP for Large Problem Area
So the issue here is that I have overconstrained the model. I am constraining the relationship between out_degree and in_degree while simultaneously constraining the actual value of ...
- 175
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