A new reduction method for the analysis of large workflow models
نویسندگان
چکیده
This paper presents a new net-reduction methodology to facilitate the analysis of large workflow models. We propose an enhanced algorithm based on reducible subnet identification which preserves both soundness and completion time distribution. Moreover we outline an approach to model the dynamic behavior of business processes by exploiting the power of a class of non-Markovian stochastic Petri net models.
منابع مشابه
A Novel Assisted History Matching Workflow and its Application in a Full Field Reservoir Simulation Model
The significant increase in using reservoir simulation models poses significant challenges in the design and calibration of models. Moreover, conventional model calibration, history matching, is usually performed using a trial and error process of adjusting model parameters until a satisfactory match is obtained. In addition, history matching is an inverse problem, and hence it may have non-uni...
متن کاملA TWO-STAGE DAMAGE DETECTION METHOD FOR LARGE-SCALE STRUCTURES BY KINETIC AND MODAL STRAIN ENERGIES USING HEURISTIC PARTICLE SWARM OPTIMIZATION
In this study, an approach for damage detection of large-scale structures is developed by employing kinetic and modal strain energies and also Heuristic Particle Swarm Optimization (HPSO) algorithm. Kinetic strain energy is employed to determine the location of structural damages. After determining the suspected damage locations, the severity of damages is obtained based on variations of modal ...
متن کاملAnalysis of Hierarchical Bayesian Models for Large Space Time Data of the Housing Prices in Tehran
Housing price data is correlated to their location in different neighborhoods and their correlation is type of spatial (location). The price of housing is varius in different months, so they also have a time correlation. Spatio-temporal models are used to analyze this type of the data. An important purpose of reviewing this type of the data is to fit a suitable model for the spatial-temporal an...
متن کاملA New Approach for Knowledge Based Systems Reduction using Rough Sets Theory (RESEARCH NOTE)
Problem of knowledge analysis for decision support system is the most difficult task of information systems. This paper presents a new approach based on notions of mathematical theory of Rough Sets to solve this problem. Using these concepts a systematic approach has been developed to reduce the size of decision database and extract reduced rules set from vague and uncertain data. The method ha...
متن کاملProviding a New Model to Improving DEA-based Models in Multi-criteria Inventory Classification (Case Study: Pars Khazar)
Abstract Objective: Many organizations use the ABC classification method to control their large amount of inventories. The most common way to classify inventories is the ABC method. In traditional ABC classification, items are only classified according to one criteria. But there are other criteria that need to be considered in the inventory classification. The purpose of this study is to prese...
متن کامل