search for: knapsack

Back in the days of DOS I had a program that I obtained from somewhere called FILL. FILL would take the name of a directory and then start writing files from that directory onto a series of floppy disks in such a way that each disk was made as full as possible, but without modifying the files that it was writing. So you might end up with disk 1 having files A B and D on them since D fitted but C

Dear all, I would like to solve a problem similar to a multiple knapsack problem and am looking for a function in R that can help me. Specifically, my situation is as follows: I have a list of n items which I would like to allocate to m groups with fixed size. Each item has a certain profit value and this profit depends on the type of group the item is in. My problem...

Hi Folks, This is not an R question as such, though it may well have an R answer. (And, in any case, this community probably knows more about most things than most others ... indeed, has probably pondered this very question). I: Given a "catalogue" of hundreds of books, where each "entry" has author and title (or equivalent ID), and also Ia) The dimensions (thickness,

...other large dependencies. The links below are how we split the package in Fedora. This may not be a suitable split for Debian, and it's probably not even the best split for Fedora, but it's here as a reference. [It'd be good to do some analysis on the largest dependent packages and a knapsack-type best division analysis.] http://pkgs.fedoraproject.org/cgit/libguestfs.git/tree/libguestfs.spec?id=c28e621afd5f78e5f55286b2f7a6fa6c3d9469ec#n840 http://pkgs.fedoraproject.org/cgit/libguestfs.git/tree/libguestfs.spec?id=c28e621afd5f78e5f55286b2f7a6fa6c3d9469ec#n244 This patch probably won'...

Hello, I am stuck with selecting the right rows from a data frame. I think the problem is rather how to select them then how to implement the R code. Consider the following data frame: df <- data.frame(ID = c(1,2,3,4,5,6,7,8,9,10), value = c(34,12,23,25,34,42,48,29,30,27)) What I want to achieve is to select 7 rows (values) so that the mean value of those rows are closest to the value of 35

Dear all, The following problem just has been submitted to me by an accountant. In his new job, he has to close some old accounts. He has yearly amounts, and a list of products that have been bought over the years, at certain prices for which he has an exhaustive record. The problem is: He does not know what product was bought this or that year (don't ask). He does not want to find back

...mber using a program like that. I'm not sure if something like that is available for Linux, and if it would handle USB (you'd have to actually look at each stick since they aren't always exactly the same size). If it helps your search, what you are looking for is an application of the knapsack algorithm. -- Chris Adams <linux at cmadams.net>

...e has been developed in such a way as to permit a complete separation between the 'engine', and the particular problem subject to combinatorial optimization. This is evident in the available examples, that come with the package, illustrating the application of QGA to different problems: knapsack, traveler salesman, and clustering. Thank you, kind regards, Giulio Barcaroli [[alternative HTML version deleted]]

...e has been developed in such a way as to permit a complete separation between the 'engine', and the particular problem subject to combinatorial optimization. This is evident in the available examples, that come with the package, illustrating the application of QGA to different problems: knapsack, traveler salesman, and clustering. Thank you, kind regards, Giulio Barcaroli [[alternative HTML version deleted]]

Hello, I would like to know if there's a package in R to solve the following problem: Let's consider a cloud of points in a n-dimensional space. Each point is associated to a specific value Vi (a real that can be positive or negative). I would like to find the n-dimensional hypercube that maximizes the sum of Vi corresponding to the points inside of the hypercube. How would you solve

Hi, Newbie question here. I've read some about how you can't power down a disk under ext3 because of the journaling writes. I also know I can mount my ext3 partitions as ext2. What about mounting the partitions as ext2 while mobile on batteries? The hard disk would spin down when it wasn't in use (if noflush, etc. has been configured). But what about data integrity when

...1abbqc showed how one website is using R to improve performance through analysis of DNS lookup times. http://bit.ly/GkKw4 offered a review of the UseR! 2009 conference overall, and http://bit.ly/BcZCW discussed some of the presentations. http://bit.ly/n788Q prompted a discussion about solving the Knapsack Problem in R. http://bit.ly/yuryk pointed to the Learning R blog, where a comparison of ggplo2 and lattice graphics is ongoing. http://bit.ly/JfZAk noted that presentations from the Rmetrics financial conference are available for download. http://bit.ly/QxXIB noted another instance of R being us...

Hi, I am currently attempting to write a small program for a randomization test (based on rank/combination) for matched pairs. If you will please allow me to introduce you to some background information regarding the test prior to my question at hand, or you may skip down to the bold portion for my issue. There are two sample sizes; the data, as I am sure you guessed, is matched into pairs and

...erted into a max-heap, because they are needed by the algorithm in decreasing-ratio order, and also because the ratio of a call site may change due to an inlining decision, which can be implemented efficiently in a heap (decrease-key). 3. Run the actual algorithm, which can be formulated as a knapsack-like problem: the call sites are chosen in a greedy fashion, based on the* benefit/cost* ratio, until the maximum cost is achieved (or no more call sites are available). After the calee is inlined, all call sites that may be affected by the inlining decision must be updated. The *benefit/cost rat...