Author: Community

On stoichiometry for the assembly of flexible tile DNA complexes

Abstract  Given a set of flexible branched junction DNA molecules with sticky-ends (building blocks), called here “tiles”, we consider
the problem of determining the proper stoichiometry such that all sticky-ends could end up connected. …

Abstract  

Given a set of flexible branched junction DNA molecules with sticky-ends (building blocks), called here “tiles”, we consider
the problem of determining the proper stoichiometry such that all sticky-ends could end up connected. In general, the stoichiometry
is not uniform, and the goal is to determine the proper proportion (spectrum) of each type of molecule within a test tube
to allow for complete assembly. According to possible components that assemble in complete complexes we partition multisets
of tiles, called here “pots”, into classes: unsatisfiable, weakly satisfiable, satisfiable and strongly satisfiable. This
classification is characterized through the spectrum of the pot, and it can be computed in PTIME using the standard Gauss-Jordan
elimination method. We also give a geometric description of the spectrum as a convex hull within the unit cube.

  • Content Type Journal Article
  • Pages 1121-1141
  • DOI 10.1007/s11047-009-9169-1
  • Authors
    • N. Jonoska, Department of Mathematics & Statistics, University of South Florida, Tampa, FL 33620, USA
    • G. L. McColm, Department of Mathematics & Statistics, University of South Florida, Tampa, FL 33620, USA
    • A. Staninska, Institute of Biomathematics and Biometry Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany

Simdist: a distribution system for easy parallelization of evolutionary computation

Abstract  This article introduces Simdist, a software tool for parallel execution of evolutionary algorithms (EAs) in a master-slave configuration on cluster architectures.
Clusters have become a cost-effective parallel solution, and the pot…

Abstract  

This article introduces Simdist, a software tool for parallel execution of evolutionary algorithms (EAs) in a master-slave configuration on cluster architectures.
Clusters have become a cost-effective parallel solution, and the potential computational capabilities are phenomenal. However,
the transition from traditional R&D on a personal computer to parallel development and deployment can be a major step. Simdist
simplifies this transition considerably, by separating the task of distributing data across the cluster network from the actual
EA-related processing performed on the master and slave nodes. Simdist is constructed in the vein of traditional Unix command
line tools; it runs in a separate process and communicates with EA child processes via standard input and output. As a result,
Simdist is oblivious to the programming language(s) used in the EA, and the EA is similarly oblivious to the internals of
Simdist.

  • Content Type Journal Article
  • Pages 185-203
  • DOI 10.1007/s10710-009-9100-7
  • Authors
    • Boye Annfelt Høverstad, Norwegian University of Science and Technology (NTNU) Department of Computer and Information Science Trondheim Norway

Melanie Mitchell: Complexity a guided tour

Melanie Mitchell: Complexity a guided tour
Content Type Journal ArticlePages 127-128DOI 10.1007/s10710-009-9097-yAuthors
Felix Streichert, Eberhard Karls Universität Tübingen Wilhelm-Schickard-Institut für Informatik Tübingen Germany

Jour…

Melanie Mitchell: Complexity a guided tour

  • Content Type Journal Article
  • Pages 127-128
  • DOI 10.1007/s10710-009-9097-y
  • Authors
    • Felix Streichert, Eberhard Karls Universität Tübingen Wilhelm-Schickard-Institut für Informatik Tübingen Germany

SIGEVOlution Volume 4, Issue 2, is now available

The new issue of the SIGEVOlution newsletter, Volume 4 Issue 2, is now available for you to download from: http://www.sigevolution.orgThe new issue features:45 Years of Evolution Strategies: Hans-Paul Schwefel Interviewed for the Genetic Argonaut BlogC…

The new issue of the SIGEVOlution newsletter, Volume 4 Issue 2, is now available for you to download from: http://www.sigevolution.org
The new issue features:
  • 45 Years of Evolution Strategies: Hans-Paul Schwefel Interviewed for the Genetic Argonaut Blog
  • CIG-2009
  • Dissertation Corner
  • Calls & calendar
The newsletter is intended to be viewed electronically.
Thanks to Pier Luca Lanzi, SIGEvolution Editor-in-Chief.

SIGEVOlution Volume 4 Issue 2

The new issue of SIGEVOlution is now available for you to download from:
http://www.sigevolution.org
The issue features:

45 Years of Evolution Strategies: Hans-Paul Schwefel Interviewed for the Genetic Argonaut Blog
CIG-2009
Dissertation Corner
Calls & calendar

The newsletter is intended to be viewed electronically.
Pier Luca Lanzi (EIC)
Related Posts

Mount Hood, Oregon

The new issue of SIGEVOlution is now available for you to download from:
http://www.sigevolution.org

The issue features:

  • 45 Years of Evolution Strategies: Hans-Paul Schwefel Interviewed for the Genetic Argonaut Blog
  • CIG-2009
  • Dissertation Corner
  • Calls & calendar

The newsletter is intended to be viewed electronically.

Pier Luca Lanzi (EIC)

Related Posts

    GECCO-2010 deadline extended

    The submission deadline for the 2010 Genetic and Evolutionary Computation Conference (GECCO-2010) has been extended to January 27, 2010. See the conference web site for more details.

    The submission deadline for the 2010 Genetic and Evolutionary Computation Conference (GECCO-2010) has been extended to January 27, 2010. See the conference web site for more details.

    Acknowledgment

    Acknowledgment
    Content Type Journal ArticlePages 3-4DOI 10.1007/s10710-009-9099-9Authors
    Lee Spector, Hampshire College School of Cognitive Science Amherst MA 01002 USA

    Journal Genetic Programming and Evolvable MachinesOnline ISSN 1573-7632Pr…

    Acknowledgment

    • Content Type Journal Article
    • Pages 3-4
    • DOI 10.1007/s10710-009-9099-9
    • Authors
      • Lee Spector, Hampshire College School of Cognitive Science Amherst MA 01002 USA

    Editorial introduction

    Editorial introduction
    Content Type Journal ArticlePages 1-2DOI 10.1007/s10710-009-9098-xAuthors
    Lee Spector, Hampshire College School of Cognitive Science Amherst MA 01002 USA

    Journal Genetic Programming and Evolvable MachinesOnline ISSN 157…

    Editorial introduction

    • Content Type Journal Article
    • Pages 1-2
    • DOI 10.1007/s10710-009-9098-x
    • Authors
      • Lee Spector, Hampshire College School of Cognitive Science Amherst MA 01002 USA

    A particle swarm optimization based memetic algorithm for dynamic optimization problems

    Abstract  Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems
    since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimizat…

    Abstract  

    Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems
    since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based
    memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework
    of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator
    and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random
    immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks
    in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic
    algorithm is robust and adaptable in dynamic environments.

    • Content Type Journal Article
    • DOI 10.1007/s11047-009-9176-2
    • Authors
      • Hongfeng Wang, School of Information Science and Engineering, Northeastern University, Shenyang, 110004 People’s Republic of China
      • Shengxiang Yang, Department of Computer Science, University of Leicester, University Road, Leicester, LE1 7RH UK
      • W. H. Ip, Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, People’s Republic of China
      • Dingwei Wang, School of Information Science and Engineering, Northeastern University, Shenyang, 110004 People’s Republic of China