We are happy to announce the release of HeuristicLab 3.3.16, which is named after the location of this year's Genetic and Evolutionary Computation Conference (​GECCO) in Prague, Czech Republic.

HeuristicLab 3.3.16 "Prague" contains the following new features:

• decision tree algorithms for regression problems
• integration of ​Google OR-Tools for writing and solving MIP/LP models
• new and much faster persistence API (​HEAL.Attic) for saving and loading files
• management of projects in HeuristicLab Hive for assigning jobs and compute resources
• upgraded to .NET Framework 4.6.1
• several other performance improvements and bug fixes

For a full list of all changes have a look at the ChangeLog.

Go to the Download page or click on the image below to get HeuristicLab 3.3.16 "Prague" now!

We are happy to announce the release of HeuristicLab 3.3.15, which is named after the location of last year's Genetic and Evolutionary Computation Conference (​GECCO) in Berlin, Germany.

HeuristicLab 3.3.15 "Berlin" contains the following new features:

• New problems:
  • Graph Coloring
• New data analysis algorithms:
  • Barnes-Hut t-SNE (C# port of Laurens van der Maaten's C++ implementation)
  • Kernel Ridge Regression
  • Elastic-net Regression (glmnet wrapper)
• Support for categorical variables for symbolic regression and multiple data analysis algorithms
• PSO improvements (compatible with standard PSO 2011)
• Extreme-point based packing algorithm for 3D bin packing
• New functionalities for data preprocessing
• New functionality for run analysis (e.g. RLD/ECDF)

For a full list of all changes have a look at the ChangeLog.

Go to the Download page or click on the image below to get HeuristicLab 3.3.15 "Berlin" now!

We are happy to announce the release of HeuristicLab 3.3.14, which we finished at this year's Genetic and Evolutionary Computation Conference (​GECCO) in Denver, CO, USA.

HeuristicLab 3.3.14 "Denver" contains the following new features:

• New problems:
  • Bin Packing
  • Probabilistic TSP
  • Multi-Objective Testfunctions
• New data analysis algorithms:
  • Gradient Boosted Regression
  • Nonlinear Regression
  • Elastic-Net
• Gradient Charts

For a full list of all changes have a look at the ChangeLog.

Go to the Download page or click on the image below to get HeuristicLab 3.3.14 "Denver" now!

The HeuristicLab development team is proud to announce the release of HeuristicLab 3.3.9.

Among others, HeuristicLab 3.3.9 contains the following new features:

• CMAES
• improved Hive server performance
• improved GP interpreter performance
• export of symbolic regression/classification solutions to Excel
• a new problem for the optimization of trading rules

For a full list of all changes in HeuristicLab 3.3.9 have a look at the ChangeLog.

Go to the Download page or click on the image below to get HeuristicLab 3.3.9 now!

Just in time for our demo at GPTP 2013, the HeuristicLab development team released HeuristicLab 3.3.8.

Among others, HeuristicLab 3.3.8 contains the following new features:

• Scatter Search
• Relevant Alleles Preserving GA (RAPGA)
• Symbolic Time-Series Prognosis
• Neighborhood Component Analysis
• Ensemble Modeling
• LM-BFGS
• Gaussian Process Regression and Least-Squares Classification
• Job Shop Scheduling
• Linux support based on Mono

For a full list of all changes in HeuristicLab 3.3.8 have a look at the ChangeLog.

Go to the Download page or click on the image below to get HeuristicLab 3.3.8 now!

Just in time for our tutorial at GECCO 2012, the HeuristicLab development team released HeuristicLab 3.3.7.

Among others, HeuristicLab 3.3.7 contains the following new features:

• new dialog to automatically create large experiments
• support for the optimization knowledge base (OKB)
• new and improved implementation of the Vehicle Routing Problem (VRP) which supports more VRP variants such as CVRP, DCVRP, CVRPTW, PDPTW, and MDCVRPTW
• lawn mower problem
• linear assignment problem and Hungarian algorithm
• benchmark problem instances: HeuristicLab now includes various libraries of published benchmark problem instances for combinatorial optimization problems (TSPLIB, QAPLIB, Taillard, Golden, Cordeau, Solomon, etc.) and regression/classification problems (Keijzer, Korns, Nguyen, real world problems, etc.)

For a full list of all changes in HeuristicLab 3.3.7 have a look at the ChangeLog.

Go to the Download page or click on the image below to get HeuristicLab 3.3.7 now!

Happy new year! The HeuristicLab development team kicked off 2012 with the brand new HeuristicLab 3.3.6 release.

One of the most exciting new features of HeuristicLab 3.3.6 is HeuristicLab Hive which provides an infrastructure for parallel and distributed computing. Hive consists of a server and computation slaves. Users can upload jobs to the Hive server which distributes the jobs among the available slaves. The slaves execute the jobs and send the result back to the server after they are finished. More information about how to install a Hive server and Hive slaves and how to use Hive in general can be found in the Howtos?.

Additional new features in HeuristicLab 3.3.6 include:

• Robust Taboo Search for the Quadratic Assignment Problem
• New Standard Algorithms for Regression and Classification (kNN, Neural Networks, Multi-Nominal Logit Regression)
• Genetic Programming Grammar Editor
• New Standard Tree-Creation Operators for Genetic Programming (Grow, Full, Ramped Half-Half)
• RunCollectionModifiers to Combine and Transform Algorithm Results
• Improved Customization and Export of Charts
• Performance Benchmarks

For a full list of all changes in HeuristicLab 3.3.6 have a look at the ChangeLog.

Go to the Download page or click on the image below to get HeuristicLab 3.3.6 now!

Recently we created a Google Group for HeuristicLab. This group provides a platform for all HeuristicLab users and developers to ask questions, share comments, post feature requests, or discuss new ideas. The group is open for everyone. Feel free to join!

More details about the group are available at ​http://groups.google.com/group/heuristiclab. To join the group, visit the page and click on "Join this group" (requires a Google account). If you do not have a Google account, please write an e-mail to ​support@heuristiclab.com and we will send you an invitation to the group. After you have joined you can contact the whole group by writing e-mails to ​heuristiclab@googlegroups.com.