# minimum vertex cover problem

I am trying to implement the minimum vertex cover problem

So here is my objective:

//minimize the number of vertices/variables

//*minimize(Σ x _{i} , i ∈ V)* (the sum is over all nodes in the graph)

cqm.set_objective(-1.5*quicksum(all_vars.values()))

And here is my constraint:*//x _{i} + x_{j} ≥ 1* for all

*(i, j) ∈ E*

for i in range(len(pair_list)):

cqm.add_constraint((all_vars[pair_list[i][0]] + all_vars[pair_list[i][1]]) >= 1)

the constraints and objectives are from this link: hvidberrrg/d-wave: Experiments with D-Wave quantum annealing (github.com)

But it does not seem to work.

I did not want to write the constraint the way i wrote it above but it is the only way Dwave accepted it.

I wanted to write it like this:

cqm.add_constraint((all_vars[pair_list[i][0]] + all_vars[pair_list[i][1]]) >= 1 for i in range(len(pair_list)))

I did not want to write the constraint the way i wrote it above but it is the only way Dwave accepted it.

I wanted to write it like this:

cqm.add_constraint((all_vars[pair_list[i][0]] + all_vars[pair_list[i][1]]) >= 1 for i in range(len(pair_list)))

I appreciate your help!

I am stuck in this part.

I am stuck in this part.

## Comments

David J(Report)Please refer to this thread:

https://support.dwavesys.com/hc/en-us/community/posts/14386974579351/comments/14415024318999

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