EvoHOT2004 will show the latest developments in the field of evolutionary algorithms applied to design automation, and will offer good opportunities for informal contact in a friendly and relaxed setting. Each accepted paper will be presented orally at the conference and published by Springer as part of EvoWorkshops2004 in the Lecture Notes in Computer Science series.

LNCS 3005, the EvoWorkshops2004 proceedings, is now available online

EvoHOT PROGRAMME DETAILS

WORKSHOP PAPERS

A Slicing Structure Representation for the Multi-Layer Floorplan Layout Problem
Johan Berntsson, Maolin Tang

Abstract:
This is a preliminary study in which we use a genetic algorithm to solve the
multiple layer floorplanning problem. The original contribution is a three dimensional slicing structure representation which, to the best of our knowledge, is the first 3D floorplan representation in the literature. In this paper we give some background on VLSI design and the floorplanning problem before describing the slicing structure representation and the genetic algorithm extensions. We present results for benchmark problems and obtain improvements on previously published results for single layer floorplanning.

Disjoint Sum of Product Minimization by Evolutionary Algorithms
Nicole Drechsler, Mario Hilgemeier, Güorschwin Fey, Rolf Drechsler

Abstract:
Recently, an approach has been presented to minimize Disjoint Sum-of-Products (DSOPs) based on Binary Decision Diagrams (BDDs). Due to the symbolic representation of cubes for large problem instances, the method is orders of magnitude faster than previous enumerative techniques. But the quality of the approach largely depends on the variable ordering of the underlying BDD. This paper presents an Evolutionary Algorithm (EA) to optimize the DSOP representation of a given Boolean function. The EA is used to find an optimized variable ordering for the BDD representation. Then the DSOP is derived from the optimized BDD using structural and symbolic techniques. Experiments are performed to adjust the parameters of the EA. Experimental results are given to demonstrate the efficiency of the approach.

Genetic Algorithms to Improve Mask and Illumination Geometries in Lithographic Imaging Systems
Tim Fühner, Andreas Erdmann, Richard Farkas, Bernd Tollkühn, Gabriella Kókai

Abstract:
This paper proposes the use of a genetic algorithm to optimize mask and illumination geometries in optical projection lithography. A fitness function is introduced that evaluates the imaging quality of arbitrary line patterns in a specified focus range. As a second criterion the manufacturability and inspectability of the mask are taken into account. With this approach optimum imaging conditions can be identified without any additional a-priori knowledge of the lithographic process. Several examples demonstrate the successful application and further potentials of the proposed concept.

Multi-Objective Genetic Manipulator Trajectory Planner
Eduardo José Solteiro Pires, Paulo B de Moura Oliveira, José António Tenreiro Machado

Abstract:
This paper proposes a multi-objective genetic algorithm to optimize a manipulator trajectory. The planner has several objectives namely the minimization of the space and join arm displacements and the energy required in the trajectory, without colliding with any obstacles in the workspace. Simulations results are presented for robots with two and three degrees of freedom, considering the optimization of two and three objectives.

Exploiting HW Acceleration for Classifying Complex Test Program Generation Problems
Ernesto Sanchez, Giovanni Squillero, Massimo Violante

Abstract:
This paper presents a complete framework to examine, evaluate and characterize an evolutionary test-program generation problem. Our methodology is based on a local analysis of the relationships between genotype and fitness. Furthermore we propose the adoption of a hardware accelerator device for speeding up program cultivation. A commercial, complex microprocessor was used as case study. Experimental analysis allows discovering the characteristics of the specific task and foreseeing the behavior of the test-program generation.

Evolutionary Design Space Exploration for Median Circuits
Lukas Sekanina

Abstract:
This paper shows that it is possible to (1) discover novel implementations of median circuits using evolutionary techniques and (2) find out suitable median circuits in case that only limited resources are available for their implementation. These problems are approached using Cartesian genetic programming and an ordinary compare--swap encoding. Combining the proposed approaches a method is demonstrated for effective exploration of the design space of median circuits under various constraints.

Co-chair: Giovanni Squillero, Politecnico di Torino <giovanni.squillero@polito.it>
Co-chair: Rolf Drechsler, University of Bremen <drechsle@informatik.uni-bremen.de>
Gabriella Kókai, Friedrich-Alexander University Erlangen-Nürnberg, Germany
Ernesto Sanchez, Politecnico di Torino, Italy
Lukás Sekanina, Brno University of Technology, Czech Republic
George D. Smith, University of East Anglia, United Kingdom
Tan Kay Chen, National University of Singapore, Republic of Singapore
Massimo Violante, Politecnico di Torino, Italy

Günther Raidl, Vienna University of Technology <raidl@ads.tuwien.ac.at>
Stefano Cagnoni, Universita' di Parma <cagnoni@ce.unipr.it>
Local chair : Ernesto Costa, University of Coimbra <ernesto@dei.uc.pt>

IEEE publishes an average of 20 papers each year where evolutionary techniques are exploited to solve design automation problems. Concurrently, the field of evolutionary computation reveals a significant interest in evolvable hardware and problems such as routing, placement, or test pattern generation.

EvoHOT2004 will show the latest developments in the field of evolutionary algorithms applied to design automation, and will offer good opportunities for informal contact in a friendly and relaxed setting. Each accepted paper will be presented orally at the conference and published by Springer in the LNCS series.

EvoHOT2004 topics cover all evolutionary computation techniques applied to design automation, including (but not limited to):

• Analog circuit design
• Automatic test pattern generation
• Built-in self test
• Evolutionary design of electronic circuits
• Evolutionary hardware design methodologies
• Evolutionary robotics
• Evolvable hardware
• Floorplanning
• Hardware/Software co-design
• Logic synthesis
• Routing
• Test program generation

High quality papers are sought on topics strongly related to genetic programming, ranging from theoretical work to innovative applications. Submissions should be a maximum of ten A4 pages and they should be sent in PDF format by email to both organisers:

Giovanni Squillero <giovanni.squillero@polito.it>
Rolf Drechsler <drechsle@informatik.uni-bremen.de>

Papers must conform to the Springer Lecture Notes in Computer Science format: http://www.springer.de/comp/lncs/authors.html.

IMPORTANT: The reviewing process will be double-blind, so please omit information about the authors in the submitted paper. The submissions will be peer reviewed by at least three members of the program committee. Manuscripts must be submitted no later than 21 November (extended deadline) 2003. Authors will be notified on the results of the review by 19 December 2003. The authors of accepted papers will have to improve their paper on the basis of the reviewers' comments and will be asked to send a camera ready version of their manuscripts by 16 January 2004.

The EvoWorkshops2004 proceedings will be
published by Spinger as part of their
Lecture Notes in Computer Science series.