Charitha Heendeniya
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Latest activity by Charitha Heendeniya-
Charitha Heendeniya commented,
Thank you. I will try that. So in general, can we say that indicator constraints perform better than bilinear and quadratic constraints?
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Charitha Heendeniya commented,
The link I sent before is broken due to the fulltop at the end. The download link again: https://www.filemail.com/d/xsadvtceoialmei
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Charitha Heendeniya commented,
Please find the log output below. The LP file is available at https://www.filemail.com/d/xsadvtceoialmei. Thread count: 10 physical cores, 12 logical processors, using up to 12 threads Optimize a...
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Charitha Heendeniya commented,
Thank you Jaromil. I tried your suggestion. H 0 0 1547.9138011 1400.00000 9.56% - 279s 0 2 1400.00000 0 35 1547.91380 1400.00000 9.56% - 282s ...
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Charitha Heendeniya commented,
Thank you very much. Yes, I missed that when I sum over the binaries, it turns out to be an integer value.I post the progress above. You see that the dual bound is stuck. By 300s, the incumbent is ...
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Charitha Heendeniya commented,
I also attach a screenshot of the post.
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Charitha Heendeniya commented,
Hello Jaromil, Here is the particular linearized constraint. self is an instance of a Gurobi model. _x is binary, _z is continuous in the range [0, 1], e_high and e_low are the big-M's I play with....
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Charitha Heendeniya created a post,
Question about linearization
AnsweredHello, This might be a simple question, but I want to really understand what is going on behind the scene. I'm trying to linearize a product between a binary and a continuous variable. The binary v...
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Charitha Heendeniya commented,
OK, I will try that. When a continuous variable is defined, I thought (-inf, _nf) bounds are implied. I missed that the default lower bound is 0 Thank you very much.
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Charitha Heendeniya commented,
Dear Jonas, Thank you for the reply. x[386,135,t2] = 0 and x[386,135,t1] = 0 because they are coming from a partial solution. So Gurobi also knows it. You are right. en[46,135] is continuous. Buddi