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9

For a table of benchmark instances on SDVRP you can have a look at Table 4 (Benchmark on known SDVRP problem instances) of Ray et al. (2014)1. More details are provided in reference [30]2 of the paper. References [1] Ray, S., Soeanu, A., Berger, J., Debbabi, M. (2014). The multi-depot split-delivery vehicle routing problem: Model and solution algorithm. ...


9

Time Series Data Library The time series data library from Rob Hyndman has hundreds (~648+) of time-series data. It depends on what you call "demand" and what you require as a "sufficiently long period of time." The entire dataset has been migrated to an R package called tsdl. It is also available on GitHub. You can find descriptions of the data in the ...


8

I was wondering if there is any repository of datasets for supply chain problems? Global Garment Supply Chain Data - A collection of import data from various retailers - Last updated: October 19, 2013, 10:23 AM (UTC-07:00) [Note: The website Datahub has 11,591 other datasets.] USAID - Supply Chain Shipment Pricing Data This data set provides supply ...


7

√Čric Taillard publishes problem sets for flow shop, job shop and open shop scheduling (from one of his papers) at http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/ordonnancement.html. Oleg Shylo publishes job shop problem sets from Demirkol et al., as well as best known solutions to both the Taillard and Demirkol problems, at http://...


7

I would just call it "planning data". I think it might be easier to convince an administrator that "planning data" needs to be recorded/captured than to sell them on "<insert techno-jargon phrase here> data". Administrators grasp what planning is (whether or not they are adept at doing it), and at some visceral level they ...


7

I would call them decision-relevant data, because most optimization problems in practice help people do decisions better, which they already do in a heuristic fashion. This puts the focus on the decision and what is needed to effectively make this decision. Alternatives would be system-describing data/system-boundary data, because the data defines the ...


6

Adhering to the rules of encapsulation, I would simply call it "parameters". If we're thinking of an optimisation model and, as you said, what changes is the number of things (number of students, number of classrooms, a table with the teachers' schedule, etc.), that's what we call usually parameters in optimisation modelling so I don't see a reason ...


5

It is possible. Although I haven't done this for a deep neural network (my experience was on a multi-layer perceptron), it shouldn't be that different procedure-wise. Considering that each neuron represents an analytical expression, it very possible to unwrap your network into one massive function. You can in principle do this using SymPy. You can walk your ...


5

AFAIK, some software such as GAMS, Lingo, AMPL and SCIP have had facilities to deal with it. For example, GAMS has a list file which contains much useful information about the problem and its solution. Also, Lingo has a graphical interface to depict the problem specifications. For example, Lingo matrix picture:


5

The following may or may not be useful for hub location problems, but is certainly applicable to many problems pertaining to the title "Strategic planning based on average values" If $X$ is a random variable for which only the mean, $\bar{X}$ is known, sometimes qualitative analysis can be performed to determine the direction of the error between 1) the ...


5

I come across the problem quite a bit (am a practitioner in a utility company building offshore wind farms), and here is my take: As Marco said, try to get as much data about the system as possible: past shipment values, domain experts giving their opinion (treat those with a pinch of salt though) etc. then incorporate this in the best way you see fit (fit ...


5

One of the PhD students in my office is working on a similar project that they called digitalization, in which they use raspberry pi and various sensors to collect the data from the machines in production line, send them to cloud and after extracting data-driven parameters, they use those parameters to estimate the down-time of the machine and control the ...


4

Instead of deep learning, you can try to use so-called "explainable machine learning", where you learn directly Boolean rules which are generally restricted to be short (of course, accuracy may suffer in this case). See, for example, this paper: https://papers.nips.cc/paper/7716-boolean-decision-rules-via-column-generation.pdf


4

Fabian, I believe many situations have this tension of strategic decisions that may turn out not to suit every operational situation; I think of locating charging stations for electric vehicles, etc. In this generality, I can only come up with general answers. Of course, robust optimization comes to mind, but these days also data-driven approaches. Don't ...


4

This might be not exactly what you are looking for but GCG (based on SCIP) has a nice visualize command that you can call after it found a decomposition (Dantzig-Wolfe or Benders). It visualizes the decomposition in its master and subproblems but also highlights the non-zero entries of the matrix. If there is no such decomposition it still shows you the non-...


3

The first step is to ascertain "reasonable" configurations of the facility being modeled. Configuration includes physical characteristics (types of machines, number of machines of each type, typical availability v. down time, etc.) as well as information about the demand patterns (types of jobs, arrival rates of jobs, typical due dates, etc.). For ...


3

I think, answers provided so far are great. When talking to professionals in the field, I second Nikos and call them "parameters" and cross my fingers they know the difference between a parameter and a variable (which is a bleeding wound between the OR profession in Industrial Engineering and OR profession in Business Administration). On the other ...


3

The usual way to check which instances are still open is to check the latest paper(s) on exact solution of the problem. The latest papers seem to be https://pubsonline.informs.org/doi/abs/10.1287/trsc.2018.0825 (SDVRP with time windows) and https://doi.org/10.1016/j.ejor.2014.04.026 (standard SDVRP).


2

You might be able to adjust my vrp generator code to generate some SDVRP problems. That way you'll immediately have road distances etc. I used it to create the Belgium road-km/road-time/air - 50-2750 visits datasets. Whatever you do, post the datasets on vrp-rep.org - we as a community should try to centralize all vrp datasets. (I am not affiliated with vrp-...


1

What you are asking for sounds somewhat similar to Alteryx (which starts at $5,195/user per year). Let's see how we can duplicate some of the look and functionality that with free tools. A demo video "Alteryx Designer in 20 Minutes" (titled "Alteryx Demo" on YouTube) is available. Here's an overview of the workflow: You asked for: "Let's say you have an ...


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