Paper: On the Performance of Master-Slave Parallelization Methods for Multi-Objective Evolutionary Algorithms - ICAISC 2013

This paper was prepared for the ICAISC 2013 conference and it is related to my current research project that has the general aim of enhancing currently available Evolutionary Computation methods employed for the multi-objective optimization of problems that rely on a very time-intensive fitness evaluation functions. Here is the abstract of the article:

This paper is focused on a comparative analysis of the performance of two master-slave parallelization methods, the basic generational scheme and the steady-state asynchronous scheme. Both can be used to improve the convergence speed of multi-objective evolutionary algorithms (MOEAs) that rely on time-intensive fitness evaluation functions. The importance of this work stems from the fact that a correct choice for one or the other parallelization method can lead to considerable speed improvements with regards to the overall duration of the optimization. Our main aim is to provide practitioners of MOEAs with a simple but effective method of deciding which master-slave parallelization option is better when dealing with a time-constrained optimization process.

You can download a preliminary version of the paper by clicking here or from my Downloads box (On the Performance of Master-Slave Parallelization Methods for MOEAs - ICAISC 2013.pdf). The same preliminary draft of the document can be previewed at the bottom of this post. The original publication is available at www.springerlink.com.

For citations please use the following BibTeX reference:

@INCOLLECTION{Zavoianu2013ICAISC,
  author = {Alexandru-Ciprian Z\u{a}voianu and Edwin Lughofer and Werner Koppelst\"{a}tter and G\"{u}nther Weidenholzer and Wolfgang Amrhein and Erich Peter Klement},
  title = {On the Performance of Master-Slave Parallelization Methods for Multi-Objective Evolutionary Algorithms},
  booktitle = {International Conference on Artificial Intelligence and Soft Computing (ICAISC 2013)},
  publisher = {Springer Berlin / Heidelberg},
  year = {2013},
  editor = {Laszek Rutkowski et al.},
  volume = {7895},
  series = {Lecture Notes in Artificial Intelligence},
  pages = {122-134},
  doi = {10.1007/978-3-642-38610-7_12}
}

Most TED talks are very good. A few are simply astonishing.

I've stumbled upon this particular gem via a Business and Culture English course I'm taking at the University (if you find it hard to follow, it also has subtitles for around 30 languages):

 

My favourite quotes - revisited

"The two most important days in your life are the day you are born and the day you find out why."
Mark Twain

"Empty pockets never held anyone back. Only empty heads and empty hearts can do that" Norman Vincent Peale  "A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects."   Robert A. Heinlein  "We are all in the gutter, but some of us are looking at the stars." Oscar Wilde  "Computers are useless. They can only give you answers." Pablo Picasso  "It is better to keep your mouth closed and let people think you are a fool than to open it and remove all doubt." Mark Twain "Illusion is the first of all pleasures." Oscar Wilde "When you play, play hard; when you work, don't play at all." Theodore Roosevelt   "Courage is what it takes to stand up and speak, Courage is also what it takes to sit down and listen." Sir Winston Churchill  "The empires of the future are the empires of the mind." Sir Winston Churchill   "Creativity is allowing yourself to make mistakes. Art is knowing which ones to keep." Scott Adams  "Insanity: doing the same thing over and over again and expecting different results." Albert Einstein

Paper: A Hybrid Soft Computing Approach for Optimizing Design Parameters of Electrical Drives - SOCO 2012

This paper was prepared for the SOCO 2012 conference and it provides some insight into my current research project that has the general aim of enhancing currently available Evolutionary Computation methods employed for the optimization of design parameters used in the prototyping process of electrical drives. The present paper is particularly related to this earlier post regarding the treatment of expensive fitness evaluation functions in Evolutionary Computation. Here is the abstract of the article:

In this paper, we are applying a hybrid soft computing approach for optimizing the performance of electrical drives where many degrees of freedom are allowed in the variation of design parameters. The hybrid nature of our approach originates from the application of multi-objective evolutionary algorithms (MOEAs) to solve the complex optimization problems combined with the integration of non-linear mappings between design and target parameters. These mappings are based on artificial neural networks (ANNs) and they are used for the fitness evaluation of individuals (design parameter vectors). The mappings substitute very time-intensive finite element simulations during a large part of the optimization run. Empirical results show that this approach finally reduces the computation time for single runs from a few days to several hours while achieving Pareto fronts with a similar high quality.

You can download a preliminary version of the paper by clicking here or from my Downloads box (A Hybrid Soft Computing Approach for Optimizing Design Parameters of Electrical Drives - SOCO 2012.pdf). The same preliminary draft of the document can be previewed at the bottom of this post. The original publication is available at www.springerlink.com.

For citations please use the following BibTeX reference:

@INCOLLECTION{ Alexandru-CiprianZavoianu2013,
  author = {Alexandru-Ciprian Z\u{a}voianu and Gerd Bramerdorfer and Edwin Lughofer and Siegfried Silber and Wolfgang Amrhein and Erich Peter Klement},
  title = {A Hybrid Soft Computing Approach for Optimizing Design Parameters of Electrical Drives},
  booktitle = {Soft Computing Models in Industrial and Environmental Applications - SOCO 2012},
  publisher = {Springer Berlin / Heidelberg},
  year = {2013},
  editor = {V\'{a}clav Sn\'{a}\u{s}el and Ajith Abraham and Emilio S. Corchado},
  volume = {188},
  series = {Advances in Intelligent Systems and Computing},
  pages = {347-358},
  doi = {10.1007/978-3-642-32922-7_36}
}

Paper: Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process - EUROCAST 2011

This paper was prepared for the EUROCAST 2011 conference and it basically contains a short summary of the work I have carried out for my Master Thesis Project. Here is the abstract of the article:

This research is focused on reducing the average size of the solutions generated by an enhanced GP process without affecting the high predictive accuracy this method exhibits when being applied on a complex, industry proposed, regression problem. As such, the effects the GP enhancements have on bloat have been studied and, finally, a bloat control system based on dynamic depth limiting (DDL) and iterated tournament pruning (ITP) was designed. The resulting bloat control system is able to improve by approx. 40% the average GP solution parsimony without impacting average solution accuracy.

You can download a preliminary version of the paper by clicking here or from my Downloads box (Improving the Parsimony of Regression Models for an Enhanced GP Process - EUROCAST 2011.pdf). The same preliminary draft of the document can be previewed at the bottom of this post. The original publication is available at www.springerlink.com.

For citations please use the following BibTeX reference:

@INCOLLECTION{Alexandru-CiprianZavoianu2012,
  author = {Alexandru-Ciprian Z\u{a}voianu and Gabriel Kronberger and Michael Kommenda and Daniela Zaharie and Michael Affenzeller},
  title = {Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process},
  booktitle = {Computer Aided Systems Theory - EUROCAST 2011},
  publisher = {Springer Berlin / Heidelberg},
  year = {2012},
  editor = {Moreno-Diaz, Roberto and Pichler, Franz and Quesada-Arencibia, Alexis},
  volume = {6927},
  series = {Lecture Notes in Computer Science},
  pages = {264-271},
  doi = {10.1007/978-3-642-27549-4_34},
}