Theory and Applications of Metaheuristic Algorithms Workshop at eurocast 2017

Theory and Applications of Metaheuristic Algorithms Workshop at eurocast 2017


Heuristic algorithms have been successfully used to attack complex real-world problems. For a large set of domains they are able to calculate approximate solutions in affordable time. However, heuristic algorithms tend to be very domain specific and suffer from a high problem dependency. In order to overcome this insufficiency various different heuristic optimization strategies are generalized resulting in metaheuristic algorithms.Nowadays metaheuristics enter more and more fields of applications ranging from telecommunications to bioinformatics including of course also other more traditional academic fields as for example continuous or combinatorial optimization. The drastic improvement of computational power and the successful implementation of advanced parallel and grid computing concepts enable efficient solving of problems that have been previously unsolved for a long period of time.Other important issues arise from the consequences of the No-Free-Lunch theorem. It is suggested to extend the power of basic algorithms by analyzing the topology and features of the search space leading to the design of self-adaptive algorithms. Hybridization, local search and specialized operators are in this context some of the major approaches leading to even more efficient algorithms in terms of computational effort and solution quality.All these developments enable the research community to tackle previously unsolvable problems in various challenging and often interdisciplinary applications.


Suggested topics for papers include but are not limited to:

  • ​New algorithmic developments
  • Theory and applications of Genetic Algorithms
  • Theory and applications of Genetic Programming
  • Other metaheuristics like Simulated Annealing, Tabu Search, Ant Colony Optimization, Particle Swarm Optimization, Scatter Search,...
  • Mathematical programming based approaches
  • Hybrid approaches
  • Parallel metaheuristics
  • Machine learning and simulation
  • Data driven modelling and prediction
  • Simulation based heuristic optimization
  • Application of simulation based soft computing

Paper Submission

An extended two pages abstract, including references in English with indication of the workshop of theintended contribution must be sent via webpage ( from May, 1, 2016 until October,31, 2016.For the extended abstract please follow the instructions for LNCS Authors given at the Springer Online web site. Authors will be notified of acceptance by December 1, 2016. Accepted Extended Abstracts will be published in a pre-Conference volume with ISBN. It is anticipated that the final selected full papers will be published in line with prior Eurocast meetings (Springer Lecture Notes in Computer Science No. 410, No. 585, No. 763, No. 1030, No. 1333, No. 1798, No. 2178, No. 2809, No. 3643, No. 4739, No.5717, and No. 9520). Full final papers for publication will be required before April 30, 2017

Important Dates

  • ​Submission Deadline (Extended Abstract): October 31, 2016
  • Acceptance Notification: December 1, 2016
  • Camera-Ready Paper Deadline: April 30, 2017

Workshop Chairs

Michael Affenzeller, Witold Jacak (University of Appl. Sciences of Upper Austria, Campus Hagenberg), Günther Raidl (Vienna University of Technology, Austria)


ECiP 2016 Talks and Slides online

In the Evolutionary Computation in Practice (ECiP) track, well-known speakers with outstanding reputation in academia and industry present background and insider information on how to establish reliable cooperation with industrial partners. They actually run companies or are involved in cooperations between academia and industry. If you attend, you will learn multiple ways to extend EC practice beyond the approaches found in textbooks. Experts in real-world optimization with decades of experience share their approaches to creating successful projects for real-world clients.

Due to many requests you can find some talks and slides of the ECiP - a part of the GECCO 2016 - now online:

You can find Michael Affenzeller's slides on "Heuristic Optimization in Production and Logistics" there too.


Visit to the GECCO Conference in Denver, Colorado, USA

Several HEAL members presented their work from 20th to 24th July at the Genetic and Evolutionary Computation Conference in Denver, Colorado, USA.

The Genetic and Evolutionary Computation Conference (GECCO 2016) presented the latest high-quality results in genetic and evolutionary computation. Topics include: genetic algorithms, genetic programming, evolution strategies, evolutionary programming, memetic algorithms, hyper heuristics, real-world applications, evolutionary machine learning, evolvable hardware, artificial life, adaptive behavior, ant colony optimization, swarm intelligence, biological applications, evolutionary robotics, coevolution, artificial immune systems, and more.

HeuristicLab 3.3.14 "Denver" Release

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!

Combinatorial Black Box Optimization Competition (GECCO'16)

We are proud to announce that HEAL member Andreas Beham scored 2nd place with his algorithm titled MemPR submitted to the 2nd Combinatorial Black Box Optimization Competition (CBBOC) at the GECCO 2016 conference in Denver, USA. MemPR competed in the track where no parameter tuning was allowed against 5 other algorithms. Only three algorithms could manage to take a lead in a different subset of the problem instances. MemPR was especially successful when applied on Ising Spin Glasses problem instances.

The top three algorithms in the category without parameter tuning were reported to be

  1. CMA-VNS2
  2. MemPR
  3. P3

The ranks were computed using the Schulze method to find the Condorcet winner.

We would like to thank the organizers of doing a great job in organizing the competition, creating the competition framework for a multitude of programming languages and carrying out all the computations. We would like to encourage everyone to consider the competition at next year's GECCO 2017.


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