similar to: Which genetic optimization package allows customized crossover and mutation operation

Hello, I noticed with different MUA (at least Thunberdird and OutlookExpress) endmost characters beeing sometimes cut-off my mails, so I assume dovecot is affected in this. Is this a known bug? Is it mayby already fixed? dovecot-0.99.10.6 on FreeBSD 5.2.1-RELEASE #1: Fri Mar 12 20:05:38 CET 2004 root at MONSTER.tektoform.lan:/usr/src/sys/i386/compile/SERVER A --

hey friends, I am using postfix on Centos4.0 as mailserver. I am looking for a global address book solution means every email client in my network whether outlook, outlookexpress, thunderbird, kmail, evolution etc. can find the user's email ids from that address book. LDAP has such feature but I am not able to find any good howto or Is there any other solution ? Please let me know if you

Hi, I'm looking for a R-package that does feature selection for PLS using a genetic optimization algorithm. I couldn't find one on CRAN and I wonder whether there is a free one. I would be very appreciative for any help. Regards Rolf

Hello all, I am trying to implement a simple Genetic Algorithm using some of the functions of R (such as lm). I am a total newbie with regard to R, but not programming or GAs. I thought I would have to do this in R but now it seems there are ways to call R functions from Java after all. (C++ would work for me too, having a compiled language should speed up the program.) Are there recommended

Dear Community, The ponyc<https://github.com/CausalityLtd/ponyc/tree/llvm37> (llvm37 branch) project is facing an issue on Windows: When optimizations are turned on (llvm 3.7.0-final and more specifically<https://github.com/CausalityLtd/ponyc/blob/llvm37/src/libponyc/codegen/genopt.cc>, opt-level 3, BBVectorize, LoopVectorize, SLPVectorize, RerollLoops, LoadCombine + a custom heap

Hello - does anyone know whether there are any packages for Mann-Kendall mutation tests in R available? The only one I could find online is this MK_mut_test: Mann-Kendall mutation test in Sibada/sibadaR: Sibada's accumulated R scripts for next probably use to avoid reinventing the wheel. (rdrr.io) <https://rdrr.io/github/Sibada/sibadaR/man/MK_mut_test.html> but there doesn't seem to

Very interesting, thanks for the forward! If you're interested in having a link posted on llvm.org, please email the llvmdev mailing list. -Chris On Jan 30, 2013, at 9:42 AM, Marcelo Sousa <marceloabsousa at gmail.com> wrote: > Dear all, > > I would like to share a paper I co-authored with Prof. Alper Sen. This > paper describes an algorithm to generate testbenches from

Dear R-users, Could someone please explain why the message printed by function stopifnot2, see below, is different from that of stopifnot itself? Thank you for your help, Vadim > stopifnot2 <- function(...) stopifnot(...) > stopifnot(F) Error: F is not TRUE > stopifnot2(F) Error: ..1 is not TRUE > version _ platform i386-pc-mingw32 arch i386 os

Hello, everybody. We are working on a tool for mutation testing. The work is still in progress and far away from being done. However, we have got some results already. And we would like to share them with you. But, let me give you a brief introduction first. ### Mutation Testing In a nutshell, Mutation Testing is a way to evaluate a quality of a test suite. The approach suggests introducing a

Dear all, I would like to share a paper I co-authored with Prof. Alper Sen. This paper describes an algorithm to generate testbenches from SystemC models represented with LLVM IR. It was accepted and presented at International Conference on Hardware/Software Codesign and System Synthesis (CODES/ISSS), 2012. A link to the paper is accessible from acm or Alper's website:

This got me into thinking. Indeed the problem is related to Windows exceptions, so I am not sure whether the bug reported<https://llvm.org/bugs/show_bug.cgi?id=24374> is actually fixed. Compiling Pony code (helloworld) that includes no exceptions does work fine (with optimizations). As soon as exceptions on windows come into play, writing the object file dies with the mentioned error in

… Also, it doesn’t appear that you are running on windows… From: David Majnemer Date: Saturday 12 September 2015 18:31 To: Sebastian Blessing Cc: Reid Kleckner, "llvm-dev at lists.llvm.org<mailto:llvm-dev at lists.llvm.org>" Subject: Re: [llvm-dev] Optimizer issues on Windows $ ~/llvm/Debug+Asserts/bin/llc try.ll $ echo $? 0 On Sat, Sep 12, 2015 at 6:39 AM, Sebastian Blessing

mcga 1.1 (machine coded genetic algorithms) package implements a genetic algorithm optimisation tool with machine coded chromosomes. The machine coded chromosomes stand for chromosomes that are not decoded and encoded. The byte representation of 'double' type variables are crossed-over and mutated. This is different from the binary coded and real coded genetic algorithms. Linux and

mcga 1.1 (machine coded genetic algorithms) package implements a genetic algorithm optimisation tool with machine coded chromosomes. The machine coded chromosomes stand for chromosomes that are not decoded and encoded. The byte representation of 'double' type variables are crossed-over and mutated. This is different from the binary coded and real coded genetic algorithms. Linux and

Hi; I have a R script that includes a call to genoud(); genoud process lasts about 4 seconds, what would be OK if I hadn't have to call it about 2000 times. This yields about 2 hours of processing. And I would like to use this script operationally; so that it should be run twice a day. It seems to me that the parallel processing option included in genoud() divides the task inside the function

Hello, I am trying to optimise a nonlinear model to derive 'best-fit' parameter esimates using the genoud function. I have been using the genetic algorithm - gafit - in order to do this, but I am getting parameter estimates that do not always reach the global minimum. I am very keen to apply genoud to optimising this model to see if my results will improve, and also out of personal

Hi R users, "genoud" function of "rgenoud" package will optimize my function. If opt = genoud(fn,2,max=TRUE,starting.value=c(1,10),........) opt$value will give the optimized value of the function, "fn". My problem is from the same opt, can I get the value of the function at the initial parameter values? I need the initial value of the function for

Hello - and sorry for a possibly stupid question, I'm just starting to learn rgenoud. I am defining a function with 5 parameters (p1, p2, p3, p4a, and p4b) and then want to optimize it using genoud. But I am doing something wrong. Before genoud is even able to run it says: "Error in p2 + 1.2 : 'p2' is missing". I assume I did not specify it right. My code is below. The task

I would like to limit the significant figures of the calibrated parameters determined by genoud() in the Rgenoud package. Below is some example output, where column 1 is model run number, columns 2-7 are the parameter values, and columns 8-12 are model fit statistics. I would like genoud to internally limit parameters to 4 decimal places as shown in this output. It is clear that the function is

Hello R users, I am trying to minimize two functions with genoud. It is actually one function with two sets of data, each of them having two unknown variables (called Vcmax and gi) which have the same value in each of the function. They are called f.1 and f.2 in the code below. My objective to minimize the functions in order to get the two variables equal in each of the functions. Furthermore, I