Tag: Natural Computing

Special issue on Nature Inspired Cooperative Strategies for Optimisation (NICSO)

Special issue on Nature Inspired Cooperative Strategies for Optimisation (NICSO)
Content Type Journal ArticleDOI 10.1007/s11047-009-9177-1Authors
N. Krasnogor, University of Catania Catania ItalyG. Nicosia, University of Catania Catania ItalyM. Pavo…

Special issue on Nature Inspired Cooperative Strategies for Optimisation (NICSO)

  • Content Type Journal Article
  • DOI 10.1007/s11047-009-9177-1
  • Authors
    • N. Krasnogor, University of Catania Catania Italy
    • G. Nicosia, University of Catania Catania Italy
    • M. Pavone, University of Catania Catania Italy
    • D. A. Pelta, University of Catania Catania Italy

Flocking based approach for data clustering

Abstract  Data clustering is a process of extracting similar groups of the underlying data whose labels are hidden. This paper describes
different approaches for solving data clustering problem. Particle swarm optimization (PSO) has been rec…

Abstract  

Data clustering is a process of extracting similar groups of the underlying data whose labels are hidden. This paper describes
different approaches for solving data clustering problem. Particle swarm optimization (PSO) has been recently used to address
clustering task. An overview of PSO-based clustering approaches is presented in this paper. These approaches mimic the behavior
of biological swarms seeking food located in different places. Best locations for finding food are in dense areas and in regions
far enough from others. PSO-based clustering approaches are evaluated using different data sets. Experimental results indicate
that these approaches outperform K-means, K-harmonic means, and fuzzy c-means clustering algorithms.

  • Content Type Journal Article
  • DOI 10.1007/s11047-009-9173-5
  • Authors
    • Abbas Ahmadi, Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Ave., Tehran, Iran
    • Fakhri Karray, Electrical and Computer Engineering Department, University of Waterloo, Waterloo, ON, Canada
    • Mohamed S. Kamel, Electrical and Computer Engineering Department, University of Waterloo, Waterloo, ON, Canada

A novel particle swarm niching technique based on extensive vector operations

Abstract  Several techniques have been proposed to extend the particle swarm optimization (PSO) paradigm so that multiple optima can
be located and maintained within a convoluted search space. A significant number of these implementations ar…

Abstract  

Several techniques have been proposed to extend the particle swarm optimization (PSO) paradigm so that multiple optima can
be located and maintained within a convoluted search space. A significant number of these implementations are subswarm-based,
that is, portions of the swarm are optimized separately. Niches are formed to contain these subswarms, a process that often
requires user-specified parameters. The proposed technique, known as the vector-based PSO, uses a novel approach to locate
and maintain niches by using additional vector operations to determine niche boundaries. As the standard PSO uses weighted
vector combinations to update particle positions and velocities, the niching technique builds upon existing knowledge of the
particle swarm. Once niche boundaries have been calculated, the swarm can be organized into subswarms without prior knowledge
of the number of niches and their corresponding niche radii. This paper presents the vector-based PSO with emphasis on its
underlying principles. Results for a number of functions with different characteristics are reported and discussed. The performance
of the vector-based PSO is also compared to two other niching techniques for particle swarm optimization.

  • Content Type Journal Article
  • DOI 10.1007/s11047-009-9170-8
  • Authors
    • I. L. Schoeman, Department of Computer Science, University of Pretoria, Lynnwood Road, Pretoria, South Africa
    • A. P. Engelbrecht, Department of Computer Science, University of Pretoria, Lynnwood Road, Pretoria, South Africa

BGSA: binary gravitational search algorithm

Abstract  Gravitational search algorithm is one of the new optimization algorithms that is based on the law of gravity and mass interactions.
In this algorithm, the searcher agents are a collection of masses, and their interactions are based…

Abstract  

Gravitational search algorithm is one of the new optimization algorithms that is based on the law of gravity and mass interactions.
In this algorithm, the searcher agents are a collection of masses, and their interactions are based on the Newtonian laws
of gravity and motion. In this article, a binary version of the algorithm is introduced. To evaluate the performances of the
proposed algorithm, several experiments are performed. The experimental results confirm the efficiency of the BGSA in solving
various nonlinear benchmark functions.

  • Content Type Journal Article
  • DOI 10.1007/s11047-009-9175-3
  • Authors
    • Esmat Rashedi, Department of Electrical Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169-133, Kerman, Iran
    • Hossein Nezamabadi-pour, Department of Electrical Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169-133, Kerman, Iran
    • Saeid Saryazdi, Department of Electrical Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169-133, Kerman, Iran

Discrete and continuous optimization based on multi-swarm coevolution

Abstract  This paper presents a novel Multi-swarm Particle Swarm Optimizer called PS2O, which is inspired by the coevolution of symbiotic species in natural ecosystems. The main idea of PS2O is to extend the single population PSO to the inter…

Abstract  

This paper presents a novel Multi-swarm Particle Swarm Optimizer called PS2O, which is inspired by the coevolution of symbiotic species in natural ecosystems. The main idea of PS2O is to extend the single population PSO to the interacting multi-swarms model by constructing hierarchical interaction topology
and enhanced dynamical update equations. With the hierarchical interaction topology, a suitable diversity in the whole population
can be maintained. At the same time, the enhanced dynamical update rule significantly speeds up the multi-swarm to converge
to the global optimum. The PS2O algorithm, which is conceptually simple and easy to implement, has considerable potential for solving complex optimization
problems. With a set of 17 mathematical benchmark functions (including both continuous and discrete cases), PS2O is proved to have significantly better performance than four other successful variants of PSO.

  • Content Type Journal Article
  • DOI 10.1007/s11047-009-9174-4
  • Authors
    • Hanning Chen, Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office III, Nanta Street 114#, Dongling District, 110016 Shenyang, China
    • Yunlong Zhu, Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office III, Nanta Street 114#, Dongling District, 110016 Shenyang, China
    • Kunyuan Hu, Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office III, Nanta Street 114#, Dongling District, 110016 Shenyang, China

The combinatorics of modeling and analyzing biological systems

Abstract  The purpose of this paper is to present a strictly mathematical model for interaction networks, to address the question of
steady-state analysis, and to outline an approach for reconstructing models from experimental data. Our expo…

Abstract  

The purpose of this paper is to present a strictly mathematical model for interaction networks, to address the question of
steady-state analysis, and to outline an approach for reconstructing models from experimental data. Our expositions require
notations and basic results from discrete mathematics. Therefore, we also introduce some elementary background material from
this field.

  • Content Type Journal Article
  • Pages 655-681
  • DOI 10.1007/s11047-009-9165-5
  • Authors
    • Annegret K. Wagler, Magdeburg Center of Systems Biology (MaCS), Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany
    • Robert Weismantel, Magdeburg Center of Systems Biology (MaCS), Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany

Optical solution for hard on average #P-complete instances (using exponential space for solving instances of the permanent)

Abstract  Optical architectures that use exponential space for solving instances of the (non-necessarily-binary) permanent are presented.
This is the first work to specifically focus on such hard on average problems. Two architectures are su…

Abstract  

Optical architectures that use exponential space for solving instances of the (non-necessarily-binary) permanent are presented.
This is the first work to specifically focus on such hard on average problems. Two architectures are suggested the first is
based on programmable masks, and the second on preprepared fixed number of masks.

  • Content Type Journal Article
  • DOI 10.1007/s11047-009-9168-2
  • Authors
    • Amir Anter, Department of Computer Science, Ben-Gurion University of the Negev, Beer Sheva, Israel
    • Shlomi Dolev, Department of Computer Science, Ben-Gurion University of the Negev, Beer Sheva, Israel

Binary to modified trinary number system conversion and vice-versa for optical super computing

Abstract  With the demand of the super fast processing and handling of huge volume of data the scientific workers in the field of computer
and optics felt the importance of optical computation with multivalued logic. One of the most importan…

Abstract  

With the demand of the super fast processing and handling of huge volume of data the scientific workers in the field of computer
and optics felt the importance of optical computation with multivalued logic. One of the most important number system suitable
for optical computation with multivalued logic is the modified trinary number (MTN) system because of its carry and borrow-free
operations. At this juncture to avail the advantages of both the Binary and MTN system the conversion from one system to another
is most important. In this paper we have communicated the conversion from Binary to MTN and vice-versa including the mixed
MTN with details of optoelectronic circuit implementation.

  • Content Type Journal Article
  • DOI 10.1007/s11047-009-9166-4
  • Authors
    • Amal K. Ghosh, Department of Applied Electronics and Instrumentation Engineering, Netaji Subhash Engineering College, Techno City, Garia, Kolkata, 700 152 India
    • Amitabha Basuray, Department of Applied Optics and Photonics, University of Calcutta, 92, A.P.C.Road, Kolkata, 700 009 India

Hybrid Petri net based modeling for biological pathway simulation

Abstract  Hybrid Petri net (HPN) is an extension of the Petri net formalism, which enables us to handle continuous information in addition
to discrete information. Firstly, this paper demonstrates how biological pathways can be modeled by th…

Abstract  

Hybrid Petri net (HPN) is an extension of the Petri net formalism, which enables us to handle continuous information in addition
to discrete information. Firstly, this paper demonstrates how biological pathways can be modeled by the integration of discrete
and continuous elements, with an example of the λ phage genetic switch system including induction and retroregulation mechanisms.
Although HPN allows intuitive modeling of biological pathways, some fundamental biological processes such as complex formation
cannot be represented with HPN. Thus, this paper next provides the formal definition of hybrid functional Petri net with extension
(HFPNe), which has high potential for modeling various kinds of biological processes. Cell Illustrator is a software tool
developed on the basis of the definition of HFPNe. Hypothesis creation by Cell Illustrator is demonstrated with the example
of the cyanobacterial circadian gene clock system. Finally, our ongoing tasks, which include the development of a computational
platform for systems biology, are presented.

  • Content Type Journal Article
  • Pages 1099-1120
  • DOI 10.1007/s11047-009-9164-6
  • Authors
    • Hiroshi Matsuno, Graduate School of Science and Engineering, Yamaguchi University, 1677-1, Yoshida, Yamaguchi 753-8512, Japan
    • Masao Nagasaki, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan
    • Satoru Miyano, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan

Boundedness analysis for open Chemical Reaction Networks with mass-action kinetics

Abstract  This paper describes the working principles of an algorithm for boundedness analysis of open Chemical Reaction Networks endowed
with mass-action kinetics. Such models can be thought of both as a special class of compartmental syste…

Abstract  

This paper describes the working principles of an algorithm for boundedness analysis of open Chemical Reaction Networks endowed
with mass-action kinetics. Such models can be thought of both as a special class of compartmental systems or a particular
type of continuous Petri Nets, in which the firing rates of transitions are not constant or preassigned, but expressed as
a function of the continuous marking of the network (function which in chemistry is referred to as the “kinetics”). The algorithm
can be applied to a broad class of such open networks, and returns, as an outcome, a classification of the possible dynamical
behaviors that are compatible with the network structure, by classifying each variable either as bounded, converging to 0
or diverging to ∞. This can be viewed as a qualitative study of Input–Output Stability for chemical networks, or more precisely,
as a classification of its possible I–O instability patterns. Our goal is to analyze the system irrespectively of values of
kinetic parameters. More precisely, we attempt to analyze it simultaneously for all possible values. Remarkably, tests on
non-trivial examples (one of which is discussed in this paper) showed that, as the kinetic constants of the network are varied,
all the compatible behaviors could be observed in simulations. Finally, we discuss and illustrate how the results relate to
previous works on the qualitative dynamics of closed reaction networks.

  • Content Type Journal Article
  • Pages 751-774
  • DOI 10.1007/s11047-009-9163-7
  • Authors
    • David Angeli, Dipartimento di Sistemi e Informatica, University of Florence, Florence, Italy