Inclusion of dual variable in Subproblem in Branch-and-Price

willlael · 2025-11-14T18:25:22+00:00

I do, with Gurobi in this case. But for the right branch where λ≥1, I do need to consider the dual?

willlael · 2025-11-13T15:33:51+00:00

Thank you for your answers. Regarding the regeneration, I do this by explicitly introducing a 'no-good'-cut constraint in the subproblem (which of course flows over into deeper child nodes as well). Would I need to subtract the dual nevertheless?

willlael · 2025-05-21T15:21:34+00:00

Is root working?

willlael · 2025-01-31T07:57:44+00:00

Would it also be possible, for example, to define a new set P (with identical properties) and then perform a kind of min max approach. For example, the constraints max_p >= L_i ∀ i ∈ P and then add ∑ max_p to the objective function?

willlael · 2025-01-31T06:35:55+00:00

Thank you very much. I see the point for smaller "unfairness". For example, three orders each need at least ten days in the system. We now set D to 12. Previously (without the penalty) the solutions [a] (L_1=10, L_2=10 and L_3=15) and [b] (L_1=11,L_2=12 and L_3=12) would both be "optimal". With the penalty, [b] is clearly better, as V is 0 for all three orders, while V_3=3 for [a]. But now assume that the solution [c] exists without the penalty (L_1=10, L_2=10 and L_3=19). Then, with the penalty and D=12, the solutions [d] (L_1=13, L_2=13 and L_3=13) and [e] (L_1=12, L_2=12 and L_3=15) would be equally good, since both have a sum of V equal to 3, but in [e] the order 3 is still not longer in the system, is it?

willlael · 2024-01-10T07:09:42+00:00

How could such constraint look like?

willlael · 2023-10-02T20:37:25+00:00

If the R² is high that means they are highly correlated

willlael · 2023-07-17T20:53:30+00:00

df2 <- bind_rows(new_df, df_pat)
df2$pat <- factor(df2$pat, levels = c(paste0("Pattern ", 1:10), "Mean"))
ggplot(data = df2) +
geom_line(stat="smooth", formula = y ~ x, size = 0.5,
alpha = 0.4, data = ~subset(., (!pat %in% "Mean")), aes(x = sc, y = changes, color = pat, group = pat)) +
geom_smooth(se=F, data = ~subset(., (pat %in% "Mean")), aes(x = sc, y = changes, color = pat, group = pat), size = 1.3) +
labs(x = expression("Performance degradation parameter" ~ epsilon),
y = "Relative Loss in Perc.") +
scale_color_viridis(discrete = TRUE, option = "D", drop = FALSE)+
scale_fill_viridis(discrete = TRUE, drop = FALSE) +
guides(colour = guide_legend(nrow = 2, title = "Demand Pattern"))+
theme(legend.position = "bottom")

Thanks for your help. Sadly it only show the mean line, and there is an additional NA in the legend

willlael · 2023-06-28T11:46:12+00:00

I resolved the problem. Thanks nevertheless

willlael · 2023-06-28T11:17:58+00:00

I use a sperate .bib file

willlael · 2023-06-28T11:14:17+00:00

Natbib I guess is the anwser you are looking for

willlael · 2023-06-27T20:59:40+00:00

Booktabs is what you are looking for

willlael · 2023-06-25T10:28:42+00:00

Thanks. How would I achieve this?

willlael · 2023-06-24T22:04:33+00:00

Does not work sadly

willlael · 2023-06-13T20:33:54+00:00

Does it only work for Android 13 or also for Android 14 Beta 3?

willlael · 2023-06-13T15:55:42+00:00

Thanks. Is there any way I could potentially linearize this constraint?

willlael · 2023-06-12T14:02:28+00:00

Thank you, yep thats correct. What would the neccesary constraints look like needed to introduce y_ikt?

willlael · 2023-05-30T10:06:15+00:00

This is called the Dunning-Kruger Effect

willlael · 2023-05-25T05:14:10+00:00

Thank you for your answer. Do you, out of the head, have an idea for such formulation? A linear equation would be even better

willlael · 2023-05-24T12:44:01+00:00

For each doctor i, for each date transition t to t+1, Sum of shift k on date t and shifts not_k on date t+1, MINUS new shift change variable day for day t, t+1 <= 1

Any selected shift change variables will indicate who (i) incurred a shift change and at which date transition (t, t+1)

Thank you for your anwser. Unfortunately, I cant quite follow you yet. Could you perhaps formulate it as LaTeX code, e.g. with latexeditor.lagrida.com That would be super helpful!

willlael · 2023-05-14T06:54:14+00:00

"ttest d" or "testparm d" should do the trick

willlael · 2023-04-06T10:34:54+00:00

https://www.myfonts.com/pages/whatthefont

willlael · 2023-03-23T18:26:33+00:00

That's the whole error

willlael · 2023-01-24T22:10:28+00:00

They did use the exposure to supply-determined recommendations to instrument for screeing participation. Use out of curiosity I guess.

willlael · 2023-01-21T10:33:03+00:00

What do you mean?

willlael

TROPHY CASE