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• Sep 29 2021 12:20
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• Mar 30 2021 11:09
spoorendonk opened #7
Simon Spoorendonk
@spoorendonk
right now we are solving model 1 with cont flows. I guess we want to goto model 2. Can you have a look at my modelling of integer flows in model 1. Does it make sense
modelling in 5 lines of code :)
Simon Spoorendonk
@spoorendonk
I am battling a little with the mapping of the model into a general MIP. I am thinking that in general you would be able to map a fractional model into a time discretized model so to take care of the transit time constraints and similar path resource? For integer flows probably the same. For binary flows one can use MTZ like constraints on the resources to ensure feasibility on path (not sure about non-disposable resource, ie., hard time windows but I think so). Comments?
I am thinking to do this under the hood and only ever expose the edge variables in the graph as you would expect for the path MIP. It would be quite inefficient for the MIP as-is but it can be improved later one and would serve as a solution checker for small examples
sorry for spamming you :)
@erohe_gitlab ^
@ErikOrm ^
Erik Hellsten
@erohe_gitlab
Hey! Ehm, hmm. I should first say that for my purposes, integer demand is not that interesting, it is more for the generality of your framework. We could say that that integrality comes in three tiers. The top tier, which is what generally tak about when I talk about integer flows, is that each commodity has to follow a single path. This is generally modelled using binary flow variables (which means that we have to multiply with the amount everywhere, as cost etc. is in $/unit.) So basically, we would just replace the continuous lambda variables with binary ones, and then we'll have to change our branching strategy a bit as branching only on design variables is no longer sufficient. The second tier, is (I believe) less common, and that is the one you are talking about. Here the flows have take integer values. So if a commodity contains 7 units, we can send 3 along one path and 4 along another, but not 3.5 and 3.5. This is of course intuitively interesting, as containers and such are technically integer, but in most applications, the loss in just treating them as continuous is very small when each commodity contains many units, which is most often the case. This is normally modelled with integer flow variables lambda_kp in {0, Q_k}, where Q_k is the number of units in commodity k. And then, yes, naturally we remove the multiplication by Q_k, as we have now rescaled the variable. Solving the subproblem, for both of those models is the same as when using continuous flow, except that we can preprocess and remove arcs with insufficient capacitiy Erik Hellsten @erohe_gitlab ... to flow all/a single unit, for the two models respectively. Then we just deal with integrality through branching in the master problem. It is probably not great to branch on the lambda variables immediately, so I suppose one would start with branching on arc commodity pairs, which I think won't affect the subproblem structure. The last tier is just the continuous flow we normally talk about. Simon Spoorendonk @spoorendonk I believe your case with a single path is the k-splitable MCF with k=1? For k =1 it can be done by putting type='B' on the graph variables. For the general k I am not sure how to model it Erik Hellsten @erohe_gitlab Hmm, that is a good question actually. I suppose you can model it by adding a binary opening-variable eta, in the master problem, for each commodity, with the constraints "sum(eta) <= k" and "lambda<= eta" Simon Spoorendonk @spoorendonk Erik Hellsten @erohe_gitlab But I don't know how that affects the subproblem structure etc. also seems a bit clumsy Simon Spoorendonk @spoorendonk that is kind of of what she does and then the eta's are replaced but it is unclear how it fits my framework when you model in edge variables Erik Hellsten @erohe_gitlab shouldn't that be fine-ish? eta lives purely in the MP, and only comes as an additional flat increase in the reduced cost for new paths? Simon Spoorendonk @spoorendonk as I read your proposal you have an eta per lambda, ie., a design variable per path? Then you limit the number of paths? Erik Hellsten @erohe_gitlab did I misunderstand it? isn't the k-splittable MCF just that you limit the number of paths for eacdh commodity? Simon Spoorendonk @spoorendonk yes and each path can carry some flow $0 \leq \lambda \leq d^k$ double$
Erik Hellsten
@erohe_gitlab
;)
Simon Spoorendonk
@spoorendonk
so a design varaible per path that you can count is the "normal" way of doing it
Erik Hellsten
@erohe_gitlab
I shall be honest and say that I don't know what the normal way is. It would work, in theory, but it might not be viable in practice. It is a lot of additional integer variables, which are painful to branch on
do we have any more elegant approaches? what does Mette do in their paper?
Simon Spoorendonk
@spoorendonk
she has $\lambda_p - u_p \eta_p \leq 0$ and $\sum_{P \in P^k} \eta_p \leq L$ for each commodity
Then she replaces the $\eta$ variables so the constraints above become $\sum_{p \in P} \frac {\lambda_p} {u_p} \leq L$
Erik Hellsten
@erohe_gitlab
$\sum_{P\in P^k}\eta_p\le L$, right?
Simon Spoorendonk
@spoorendonk
yes
Erik Hellsten
@erohe_gitlab
ok, so she does just that. Probably means that there are no easy other way
:(
Simon Spoorendonk
@spoorendonk
$u_p = \min_{u_e, e \in p}$
probably not. Replacing the constraints is a relaxation of the original k-splittalbe problem. Then you need to do some fancy branching to get a valid IP solution
hmm. I will stick with the integer flows for now. And the k=1 case
Erik Hellsten
@erohe_gitlab
I cannot yet see the brilliance in replacing the eta-variables

hmm. I will stick with the integer flows for now. And the k=1 case

Seems reasonable = )

Simon Spoorendonk
@spoorendonk

I cannot yet see the brilliance in replacing the eta-variables

you get a lambda only problem, but it is a ralxation

Erik Hellsten
@erohe_gitlab
haha, sweet. I started writing some comments on the models you sent in the link, but it changed as I wrote ^^
The first model seems fine. Though it is very hard to write the transit time constraints for the edge formulation. I'm also a bit curious to whether limiting the flow on each arc for a commodity to be integer, is strictly identical to limiting the flow on each path to be integer. It is easy to find a counter-example, but I could be that they have the same space of optimal solutions
Erik Hellsten
@erohe_gitlab
in the second model, starting with "under the hood", the first constraint is probably unnecessary, and z should be integer, not binary, right?
Simon Spoorendonk
@spoorendonk
the transit time constraints are crap in a edge formulation. The good thin with flowty is you never need to actually write them, just fill in the m.addResourceDisposable function when modelling.
Erik Hellsten
@erohe_gitlab
yeah, exactly =) the main reason I'm working with CG in the first place = )
Simon Spoorendonk
@spoorendonk
not entirely sure about the integer bounds n edges either
Erik Hellsten
@erohe_gitlab
without transit times, I feel rather certain that any solution that satisfies integrality on every edge, has an equivalen solution which satisfies integraility for every path. With transit-time constraints, it is less obvious
Simon Spoorendonk
@spoorendonk
yep change z to Z
Simon Spoorendonk
@spoorendonk
so for an integer variable in subproblem you always get {0,1} lambdas, however if discretize the suproblem and introduce identical suproblems with binary variables you get integer lambdas
for continuous you can do the same with [0,1] intervals (assuming your variable ub is integer)
I think...