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Hi there! The objective of the Cumulative Traveling Salesman Problem (CTSP) is to minimize the sum of arrival times at customers, instead of the total travelling time. This is different than minimizin…
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In general, it seems that retraction allows a limited amount of oozeless travel time, and the amount of ooze/error then starts increasing proportionally (but not linearly) with travel times beyond tha…
ghost updated
3 years ago
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- [x] Levantar los servicios: minikube, kale y kubeflow.
- [x] Realizar lanzamientos con diferentes valores de parámetros del paquete desarrollado (problema de optimización convexa)
* Cambiar punto…
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**What language and solver does this apply to?**
C++. Routing.
**Describe the problem you are trying to solve.**
I'd like to build and use OR-Tools' routing libraries (specifically traveling …
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**Is your feature request related to a problem? Please describe.**
As adviser would grow, it might become hard to maintain the relative order of pipeline units - boots, sieves, steps, strides and w…
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Hi!
First of all I would like to say awesome job on this project, really impressive work.
I'm considering using this repository for my master thesis project but would like to ask one question firs…
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**Programar Nuevo Método Numérico**
- [x] Analizar en Scrum Session y valorar modificar nuestro método numérico de optimización convexa en Python.
- [x] Seleccionar datasets para test.
**Re-progr…
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### Current Behaviour:
It seems that prepare scripts are now run in parallel, which means that if:
* `A` depends on `B`
* `B`'s `prepare` script takes some time. e.g. runs `tsc`
* `A` use…
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Consider the following path finding problem (which may be seen as a variant of the _Traveling Salesman_):
Let G be a graph (possibly complete) whose nodes are divided into clusters. Let us suppose …
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Originally reported on Google Code with ID 71
```
While attempting to solve the TSP for multiple sets of points (by looping over all the
sets and calling the the constraint solver on each set), an er…