2,985 research outputs found
Abridged Petri Nets
A new graphical framework, Abridged Petri Nets (APNs) is introduced for
bottom-up modeling of complex stochastic systems. APNs are similar to
Stochastic Petri Nets (SPNs) in as much as they both rely on component-based
representation of system state space, in contrast to Markov chains that
explicitly model the states of an entire system. In both frameworks, so-called
tokens (denoted as small circles) represent individual entities comprising the
system; however, SPN graphs contain two distinct types of nodes (called places
and transitions) with transitions serving the purpose of routing tokens among
places. As a result, a pair of place nodes in SPNs can be linked to each other
only via a transient stop, a transition node. In contrast, APN graphs link
place nodes directly by arcs (transitions), similar to state space diagrams for
Markov chains, and separate transition nodes are not needed.
Tokens in APN are distinct and have labels that can assume both discrete
values ("colors") and continuous values ("ages"), both of which can change
during simulation. Component interactions are modeled in APNs using triggers,
which are either inhibitors or enablers (the inhibitors' opposites).
Hierarchical construction of APNs rely on using stacks (layers) of submodels
with automatically matching color policies. As a result, APNs provide at least
the same modeling power as SPNs, but, as demonstrated by means of several
examples, the resulting models are often more compact and transparent,
therefore facilitating more efficient performance evaluation of complex
systems.Comment: 17 figure
Batch Deterministic and Stochastic Petri Nets and Transformation Analysis Methods
International audienc
Multi-objective model for optimizing railway infrastructure asset renewal
Trabalho inspirado num problema real da empresa Infraestruturas de Portugal, EP.A multi-objective model for managing railway infrastructure asset renewal is presented. The model aims to optimize three objectives, while respecting operational constraints: levelling investment throughout multiple years, minimizing total cost and minimizing work start postponements. Its output is an optimized intervention schedule. The model is based on a case study from a Portuguese infrastructure management company, which specified the objectives and constraints, and reflects management practice on railway infrastructure. The results show that investment levelling greatly influences the other objectives and that total cost fluctuations may range from insignificant to important, depending on the condition of the infrastructure. The results structure is argued to be general and suggests a practical methodology for analysing trade-offs and selecting a solution for implementation.info:eu-repo/semantics/publishedVersio
SIMULATING EXOGENOUS SHOCKS IN COMPLEX SUPPLY NETWORKS USING MODULAR STOCHASTIC PETRI NETS
Almost all major companies are embedded in complex, global supply networks, consisting of multiple nested supply chains, and building up a high level of complexity. Exogenous shocks on these networks (e.g. natural disasters) can directly and indirectly impact companies and even cause their entire supply network to fail. However, today it is extremely difficult for a company to predict the actual impact of an exogenous shock on its supply network. Hence, companies are not able to identify adequate counteractive measures. Therefore safeguarding measures are oftentimes insufficient or even counterproductive. This paper deals with modelling, analyzing and quantifying impacts of exogenous shocks on supply networks using Petri Nets. It provides means to simulate the vulnerability of different network constellations regarding exogenous influences. In order to evaluate the proposed method, we simulate different intensities of an exogenous shock delaying the delivery for an exemplary supply network. We thereby illustrate which results could be yielded from a real-world application. For our exemplary network we find that the marginal effect of a disruption declines with an increasing intensity of shock. Moreover, the impact of shocks can be mitigated by appropriate counteractive measures like in this example by an increased safety margin of stock
Predictive Process Monitoring Methods: Which One Suits Me Best?
Predictive process monitoring has recently gained traction in academia and is
maturing also in companies. However, with the growing body of research, it
might be daunting for companies to navigate in this domain in order to find,
provided certain data, what can be predicted and what methods to use. The main
objective of this paper is developing a value-driven framework for classifying
existing work on predictive process monitoring. This objective is achieved by
systematically identifying, categorizing, and analyzing existing approaches for
predictive process monitoring. The review is then used to develop a
value-driven framework that can support organizations to navigate in the
predictive process monitoring field and help them to find value and exploit the
opportunities enabled by these analysis techniques
Task sequence planning in a robot workcell using AND/OR nets
An approach to task sequence planning for a generalized robotic manufacturing or material handling workcell is described. Given the descriptions of the objects in this system and all feasible geometric relationships among these objects, an AND/OR net which describes the relationships of all feasible geometric states and associated feasibility criteria for net transitions is generated. This AND/OR net is mapped into a Petri net which incorporates all feasible sequences of operations. The resulting Petri net is shown to be bounded and have guaranteed properties of liveness, safeness, and reversibility. Sequences are found from the reachability tree of the Petri net. Feasibility criteria for net transitions may be used to generate an extended Petri net representation of lower level command sequences. The resulting Petri net representation may be used for on-line scheduling and control of the system of feasible sequences. A simulation example of the sequences is described
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