[FRIAM] Optimization problem

[Marcus Daniels]

And if you want to know how it works, I suggest SCIP.   https://scip.zib.de/

From: Friam <friam-bounces at redfish.com> on behalf of Pieter Steenekamp <pieters at randcontrols.co.za>
Reply-To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com>
Date: Friday, September 20, 2019 at 12:52 PM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com>
Subject: Re: [FRIAM] Optimization problem

Two possible approaches are:
a) Solve the problem yourself. Use one or a combination of standard algorithms ( eg you mentioned linear programming and greedy algorithms, there are many more of course) and/or your own custom algorithm. If you wish to go this route and want to learn about the subject, I recommend the series of MOOCS by Stanford's Tim Roughgarden https://www.coursera.org/specializations/algorithms
Or, I think yours is probably a knapsack -type problem and the MOOC https://www.coursera.org/learn/discrete-optimization covers that relatively well.
b) But if you just want to get the solution you can use optimization software like https://www.ibm.com/za-en/products/ilog-cplex-optimization-studio (they have a free edition that will be good enough for your application) will solve it for you without you necessarily knowing how the software does it.

On Fri, 20 Sep 2019 at 21:00, Gary Schiltz <gary at naturesvisualarts.com<mailto:gary at naturesvisualarts.com>> wrote:
I'd like advice on possible ways to solve the following problem
(plumbers must surely face this all the time). I need to cut a set of
metal tubes of varying lengths from standard length (6 meter)
galvanized conduit stock. The goal is to find the number of tubes I
need to buy, and the order of cuts to produce the minimum amount of
leftover, unused tube.  I'm interested in what types of solutions
people use for similar 1-dimensional problems, e.g. linear
programming, greedy algorithms, etc. (I've been Googling). I'm only
looking to cut around 15-25 pieces, so my gut feeling is that an
exhaustive search of all possible solutions, though probably NP-hard,
would be feasible to perform. Working programs, as well as libraries
in any language would be a bonus.

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