Geneva Optimization 0.9.11 "Route de Chamonix"

Milestone information

Geneva Optimization
Code name:
Route de Chamonix
Release registered:
No. Drivers cannot target bugs and blueprints to this milestone.  

Download RDF metadata


Assigned to you:
No blueprints or bugs assigned to you.
1 Ruediger Berlich
No blueprints are targeted to this milestone.
1 Fix Released

Download files for this release

After you've downloaded a file, you can verify its authenticity using its MD5 sum or signature. (How do I verify a download?)

File Description Downloads
download icon geneva-v0.9.11-ReleaseNotes.txt (md5, sig) Geneva v0.9.11 Release Notes 7
last downloaded 49 weeks ago
download icon geneva-v0.9.11.tgz (md5, sig) Geneva v0.9.11 (Route de Chamonix) 12
last downloaded 24 weeks ago
Total downloads: 19

Release notes 

Geneva Optimization Library

* Version 0.9.11, "Route de Chamonix" - August 14, 2013

See the Changelog for the individual changes.


View the full changelog

The main changes for this release include:
 - Added a parameter scan algorithm.
 - Separated Simulated Annealing from Evolutionary Algorithms, making
   it a first-class citizen.
 - Separated multi-populations from Evolutionary Algorithms, making
   them a first class citizen.
 - Evolutionary Algorithms are now based on GParameterSet (just like all
   other "basic" optimization algorithms, except for multi-populations).
 - Reworked the entire broker architecture (GBrokerConnectorT was replaced
   by GBrokerConnector2T, and the GBrokerT class as well as the
   GAsioTCPConsumerT classes have been refactored).
 - The broker, as implemented, now acts solely on GParameterSet-derivatives.
   This simplifies the architecture.
 - Renamed GIndividual to the more fitting "GOptimizableEntity".
 - Removed the deprecated GIndividualFactoryT class in favor of the more
   general GFactoryT.
 - Gave optimization algorithm factories a common base class so generic
   access becomes easier.
 - Added global stores for GParameterSet-based consumers, optimization
   algorithms and corresponding monitor classes.
 - GParameterSet and GOptimizableEntity no longer depend on any specific
   optimization algorithms. As a consequence, all major concepts are now
   separated from each other, allowing for a far more independent development
   style. Adding new algorithms and also consumers has become far easier.
 - Gave GParameterBase objects a name to facilitate work with the
   GExternalEvaluatorIndividual. A name to a parameter makes it much easier
   to work with XML files and to identify the important variables.
 - Simplified the optimization monitor infrastructure.
 - Added pluggable optimization monitors that allow to easily monitor
   common properties of all optimization algorithms. In this context,
   added a monitor that allows to plot one or two variables together with
   their fitness for all individuals touched during the optimization.
 - Centralized conversion of smart pointers using a Gem::Common function.
 - Removed non-portable "long double" functions from
 - Moved GConstrainedValueLimitT<T> from "max()" to "lowest()/highest()".
 - Added a simple logging framework, including exception handling, that
   allows to stream information to be logged.
 - Gave gemfony_error_condition the ability to be streamed.
 - Removed the deprecated utilities directory and application.
 - Removed most manual creation of ROOT output files in favor
   of GPlotDesigner.
 - Gave GPlotDesigner the ability to create 3D output through a new
   class GGraph3D.
 - Gave GPlotDesigner the ability to add more than one plot to the
   same sub-canvas.
 - Removed the deprecated Go class in favor of Go2 and updated all examples.
 - Made Go2 independent from specific optimization algorithms and consumers,
   thus broadening its scope. Note that during this rework, also most
   command line parameters have been changed, and that command line
   parameters specific to consumers are extracted at run-time from each
   consumer. If you are running Geneva through a script, this might mean
   that you need to adapt this script.
 - Added a new example "GStarter" meant as a starting point for the
   users' own projects.
 - Added an example that illustrates meta-optimization (i.e. usage of
   an evolutionary algorithm to optimize the configuration parameters
   of an optimization algorithm.
 - Added pluggable objects that allow to check parameter sets for validity,
   to be used in an infrastructure for dealing with multi-parameter constraints.
 - Instrumented most Geneva optimization classes with C++11 override
   statements, wrapped into defines so the code can be used with
   C++98-compilers. This allows to rule out a further class of errors,
   hence making the code more robust.
 - Ported to MacOS X (still highly experimental).
 - Ported to Boost 1.54.

Recommended version of Boost: 1.54

0 blueprints and 1 bug targeted

Bug report Importance Assignee Status
1082899 #1082899 GConstrainedInt32Object jumps from lowest value to highest value when mutation reduces the value 3 High Ruediger Berlich  10 Fix Released
This milestone contains Public information
Everyone can see this information.