Submit your research to the International Journal "Notes on Intuitionistic Fuzzy Sets". Contact us at nifs.journal@gmail.com

Call for Papers for the 27th International Conference on Intuitionistic Fuzzy Sets is now open!
Conference: 5–6 July 2024, Burgas, Bulgaria • EXTENDED DEADLINE for submissions: 15 APRIL 2024.

Generalized nets: Difference between revisions

From Ifigenia, the wiki for intuitionistic fuzzy sets and generalized nets
Jump to navigation Jump to search
(start this stub)
 
(add new sections)
Line 1: Line 1:
'''Generalized nets''' (''GNs'') constitute a discrete tool for universal description of adaptable, flexible, structured and reusable models of complex systems with many different and interacting components, not necessarily of the homogeneous structure and origin, usually involved in parallel, simultaneous activities. Generalized nets represent a significant extension and generalization of the concept of [[Petri nets]], as well as of other [[Extensions of Petri nets|Petri nets extensions and modifications]].
'''Generalized nets''' (''GNs'') constitute a discrete tool for universal description of adaptable, flexible, structured and reusable models of complex systems with many different and interacting components, not necessarily of the homogeneous structure and origin, usually involved in parallel, simultaneous activities. Generalized nets represent a significant extension and generalization of the concept of [[Petri nets]], as well as of other [[Extensions of Petri nets|Petri nets extensions and modifications]].


== Components of a generalized net ==
A generalized net consists of:
A generalized net consists of:
* a static structure,
* a static structure,
Line 8: Line 9:
The '''''static structure''''' consists of objects called ''[[transition]]s'', which have input and output ''[[place]]s''. Two transitions can share a place, but every place can be an input of at most one transition and can be an output of at most one transition.
The '''''static structure''''' consists of objects called ''[[transition]]s'', which have input and output ''[[place]]s''. Two transitions can share a place, but every place can be an input of at most one transition and can be an output of at most one transition.


The '''''dynamic structure''''' consists of ''[[token]]s'', which act as information carriers and can occupy a single place at every moment of the GN execution. The tokens pass through the transition from one input to another output place; such an ordered pair of places is called ''[[transition arc]]''. The tokens' movement is governed by conditions (''predicates''), contained in the [[predicate matrix]] of the transition.
The '''''dynamic structure''''' consists of ''[[token]]s'', which act as information carriers and can occupy a single place at every moment of the GN execution. The tokens pass through the transition from one input to another output place; such an ordered pair of places is called ''[[transition arc]]''. The tokens' movement is governed by conditions (''predicates''), contained in the [[predicate matrix]] of the transition.  


The information carried by a token is contained in its [[token characteristics|characteristics]], which can be viewed as an associative array of characteristic names and values. The values of the token characteristics change in time according to specific rules, called ''[[characteristic function]]s''. Every place possesses at most one characteristic function, which assigns new characteristics to the incoming tokens.
The information carried by a token is contained in its [[token characteristics|characteristics]], which can be viewed as an associative array of characteristic names and values. The values of the token characteristics change in time according to specific rules, called ''[[characteristic function]]s''. Every place possesses at most one characteristic function, which assigns new characteristics to the incoming tokens. Apart from movement in the net and change of the characteristics, tokens can also split and merge in the places.


The '''''temporal components''''' describe the time scale of GN execution. ''Temporal conditions'' control the transitions' moments of activation and duration of active state. Various other tools for fine tuning of the GN functioning are provided in the form of ''priorities'' of separate transitions, places and tokens, as well as ''capacities'' of places and transitions arcs.
The '''''temporal components''''' describe the time scale of GN execution. ''Temporal conditions'' control the transitions' moments of activation and duration of active state. Various other tools for fine tuning of the GN functioning are provided in the form of ''priorities'' of separate transitions, places and tokens, as well as ''capacities'' of places and transitions arcs.
=== Graphic representation ===


== Formal description ==
== Formal description ==
== Types of generalized nets ==
=== Algorithms for tokens transfer ===
 
== Reduced generalized nets ==
== Extended generalized nets ==
 
== Theoretical aspects of generalized nets ==
=== Algebraic aspect ===
=== Topological aspect ===
=== Logical aspect ===
=== Functional aspect ===
* Global operators
* Local operators
* Hierarchical operators
* Reducing operators
* Extending operators
* Dynamic operators
 
== Construction of generalized nets ==
== Construction of generalized nets ==
== Modelling and simulation ==
== Modelling and simulation ==

Revision as of 23:02, 2 November 2008

Generalized nets (GNs) constitute a discrete tool for universal description of adaptable, flexible, structured and reusable models of complex systems with many different and interacting components, not necessarily of the homogeneous structure and origin, usually involved in parallel, simultaneous activities. Generalized nets represent a significant extension and generalization of the concept of Petri nets, as well as of other Petri nets extensions and modifications.

Components of a generalized net

A generalized net consists of:

  • a static structure,
  • a dynamic structure,
  • temporal components.

The static structure consists of objects called transitions, which have input and output places. Two transitions can share a place, but every place can be an input of at most one transition and can be an output of at most one transition.

The dynamic structure consists of tokens, which act as information carriers and can occupy a single place at every moment of the GN execution. The tokens pass through the transition from one input to another output place; such an ordered pair of places is called transition arc. The tokens' movement is governed by conditions (predicates), contained in the predicate matrix of the transition.

The information carried by a token is contained in its characteristics, which can be viewed as an associative array of characteristic names and values. The values of the token characteristics change in time according to specific rules, called characteristic functions. Every place possesses at most one characteristic function, which assigns new characteristics to the incoming tokens. Apart from movement in the net and change of the characteristics, tokens can also split and merge in the places.

The temporal components describe the time scale of GN execution. Temporal conditions control the transitions' moments of activation and duration of active state. Various other tools for fine tuning of the GN functioning are provided in the form of priorities of separate transitions, places and tokens, as well as capacities of places and transitions arcs.

Graphic representation

Formal description

Algorithms for tokens transfer

Reduced generalized nets

Extended generalized nets

Theoretical aspects of generalized nets

Algebraic aspect

Topological aspect

Logical aspect

Functional aspect

  • Global operators
  • Local operators
  • Hierarchical operators
  • Reducing operators
  • Extending operators
  • Dynamic operators

Construction of generalized nets

Modelling and simulation

Software implementation of generalized nets

See also

References

Ifigenia stub This article is a stub. You can help Ifigenia by expanding it.