id: 06058621
dt: a
an: 06058621
au: Balint, Adrian; Diepold, Daniel; Gall, Daniel; Gerber, Simon; Kapler,
    Gregor; Retz, Robert
ti: EDACC ‒ an advanced platform for the experiment design, administration
    and analysis of empirical algorithms.
so: Coello Coello, Carlos A. (ed.), Learning and intelligent optimization. 5th
    international conference, LION 5, Rome, Italy, January 17‒21, 2011.
    Selected papers. Berlin: Springer (ISBN 978-3-642-25565-6/pbk). Lecture
    Notes in Computer Science 6683, 586-599 (2011).
py: 2011
pu: Berlin: Springer
la: EN
cc: 
ut: 
ci: 
li: doi:10.1007/978-3-642-25566-3_46
ab: Summary: The design, execution and analysis of experiments using heuristic
    algorithms can be a very time consuming task in the development of an
    algorithm. There are a lot of problems that have to be solved
    throughout this process. To speed up this process we have designed and
    implemented a framework called EDACC, which supports all the tasks that
    arise throughout the experimentation with algorithms. A graphical user
    interface together with a database facilitates archiving and management
    of solvers and problem instances. It also enables the creation of
    complex experiments and the generation of the computation jobs needed
    to perform the experiment. The task of running the jobs on an arbitrary
    computer system (or computer cluster or grid) is taken by a compute
    client, which is designed to increase computation throughput to a
    maximum. Real-time monitoring of running jobs can be done with the GUI
    or with a web frontend, both of which provide a wide variety of
    descriptive statistics and statistic testing to analyze the results.
    The web frontend also provides all the tools needed for the
    organization and execution of solver competitions.
rv: