Fuzzy Multiple Criteria Workflow Robustness and Resiliency Modeling with Petri Nets

2011 ◽  
Vol 1 (4) ◽  
pp. 72-90 ◽  
Author(s):  
Madjid Tavana ◽  
Timothy E. Busch ◽  
Eleanor L. Davis
Keyword(s):  
Petri Nets ◽  
Workflow Management ◽  
Multiple Criteria ◽  
Self Healing ◽  
Military Operations ◽  
Tight Coupling ◽  
Workflow Systems ◽  
Sustainability Index ◽  
Wide Range ◽  
High Level

The increasing complexity and tight coupling between people and computer systems in military operations has led to improved efficiency, as well as greater vulnerability due to system failure. Careful management of workflow systems can minimize operational vulnerability in command and control. Tavana et al. (2011) developed a workflow management framework capable of both modeling structure and providing a wide range of quantitative analysis with high-level Petri nets (PNs). The framework is based on a sustainability index that captures the concepts of self-protecting and self-healing systems. This index uses crisp numerical values to measure the robustness and resiliency of the system. However, the observed values of data in real-world military operations are often imprecise or vague. These inexact data can be represented by fuzzy numbers to reflect the decision makers’ intuition and subjective judgments. In this paper, the authors extend this model to a fuzzy framework by proposing a new fuzzy workflow modeling system with PNs. The new model plots the fuzzy robustness and resiliency measures in a Cartesian coordinate system and derives an overall fuzzy sustainability index for the system based on the theory of displaced ideals. The proposed model also considers multiple criteria to produce this fuzzy index.

Modeling Operational Robustness and Resiliency with High-Level Petri Nets

2011 ◽  
Vol 1 (2) ◽  
pp. 17-38 ◽  
Author(s):  
Madjid Tavana ◽  
Timothy E. Busch ◽  
Eleanor L. Davis
Keyword(s):  
Petri Nets ◽  
Workflow Management ◽  
The United States ◽  
Self Healing ◽  
Military Operations ◽  
Tight Coupling ◽  
Modeling Framework ◽  
Workflow Systems ◽  
Wide Range ◽  
High Level

Military operations are highly complex workflow systems that require careful planning and execution. The interactive complexity and tight coupling between people and technological systems has been increasing in military operations, which leads to both improved efficiency and a greater vulnerability to mission accomplishment due to attack or system failure. Although the ability to resist and recover from failure is important to many systems and processes, the robustness and resiliency of workflow management systems has received little attention in literature. The authors propose a novel workflow modeling framework using high-level Petri nets (PNs). The proposed framework is capable of both modeling structure and providing a wide range of qualitative and quantitative analysis. The concepts of self-protecting and self-healing systems are captured by the robustness and resiliency measures proposed in this study. The proposed measures are plotted in a Cartesian coordinate system; a classification scheme with four quadrants (i.e., possession, preservation, restoration, and devastation) is proposed to show the state of the system in terms of robustness and resiliency. The authors introduce an overall sustainability index for the system based on the theory of displaced ideals. The application of the methodology in the evaluation of an air tasking order generation system at the United States Air Force is demonstrated.

Modeling Operational Robustness and Resiliency with High-Level Petri Nets

2012 ◽  
pp. 170-191
Author(s):  
Madjid Tavana ◽  
Timothy E. Busch ◽  
Eleanor L. Davis
Keyword(s):  
Petri Nets ◽  
Workflow Management ◽  
The United States ◽  
Self Healing ◽  
Military Operations ◽  
Tight Coupling ◽  
Workflow Systems ◽  
System A ◽  
Cartesian Coordinate ◽  
High Level

Military operations are highly complex workflow systems that require careful planning and execution. The interactive complexity and tight coupling between people and technological systems has been increasing in military operations, which leads to both improved efficiency and a greater vulnerability to mission accomplishment due to attack or system failure. Although the ability to resist and recover from failure is important to many systems and processes, the robustness and resiliency of workflow management systems has received little attention in literature. The authors propose a novel workflow modeling framework using high-level Petri nets (PNs). The proposed framework is capable of both modeling structure and providing a wide range of qualitative and quantitative analysis. The concepts of self-protecting and self-healing systems are captured by the robustness and resiliency measures proposed in this study. The proposed measures are plotted in a Cartesian coordinate system; a classification scheme with four quadrants (i.e., possession, preservation, restoration, and devastation) is proposed to show the state of the system in terms of robustness and resiliency. The authors introduce an overall sustainability index for the system based on the theory of displaced ideals. The application of the methodology in the evaluation of an air tasking order generation system at the United States Air Force is demonstrated.

Fuzzy Multiple Criteria Workflow Robustness and Resiliency Modeling with Petri Nets

2012 ◽  
pp. 192-211
Author(s):  
Madjid Tavana ◽  
Timothy E. Busch ◽  
Eleanor L. Davis
Keyword(s):  
Petri Nets ◽  
Workflow Management ◽  
Multiple Criteria ◽  
Self Healing ◽  
Military Operations ◽  
Tight Coupling ◽  
Sustainability Index ◽  
Inexact Data ◽  
Fuzzy Index ◽  
Cartesian Coordinate

The increasing complexity and tight coupling between people and computer systems in military operations has led to improved efficiency, as well as greater vulnerability due to system failure. Careful management of workflow systems can minimize operational vulnerability in command and control. Tavana et al. (2011) developed a workflow management framework capable of both modeling structure and providing a wide range of quantitative analysis with high-level Petri nets (PNs). The framework is based on a sustainability index that captures the concepts of self-protecting and self-healing systems. This index uses crisp numerical values to measure the robustness and resiliency of the system. However, the observed values of data in real-world military operations are often imprecise or vague. These inexact data can be represented by fuzzy numbers to reflect the decision makers’ intuition and subjective judgments. In this paper, the authors extend this model to a fuzzy framework by proposing a new fuzzy workflow modeling system with PNs. The new model plots the fuzzy robustness and resiliency measures in a Cartesian coordinate system and derives an overall fuzzy sustainability index for the system based on the theory of displaced ideals. The proposed model also considers multiple criteria to produce this fuzzy index.

scholarly journals RE-CONFIGURING WORKFLOW MANAGEMENT SYSTEMS TO FACILITATE A "SMOOTH FLOW OF WORK"

2007 ◽  
Vol 16 (02) ◽  
pp. 155-175 ◽  
Author(s):  
H. A. REIJERS ◽  
S. POELMANS
Keyword(s):  
Workflow Management ◽  
Workflow Technology ◽  
Workflow Systems ◽  
Financial Organization ◽  
Smooth Flow ◽  
Production Type ◽  
Workflow System ◽  
Starting Point ◽  
Wide Range ◽  
Flexible Application

The image of workflow systems as being context-insensitive technology, hindering rather than supporting people in performing their work may still exist at present. This impression is also raised in the well-known and often cited case study within Establishment Printers. Using this case as a starting point, this paper presents an analysis of more recent workflow implementations to support the view that modern workflow systems are widely applied in the services industry and are considered useful by performers to support their way of working. In cases where the introduction of workflow technology initially disrupted the flow of work, a wide range of configuration options was available to mend such situations. A detailed analysis of a workflow implementation in a Belgian financial organization clearly shows that re-configuration decisions, like a finer step granularity, can transform a pre-structured production-type workflow system into a flexible application allowing and supporting a smooth flow of work.

scholarly journals Workflow Systems for Science: Concepts and Tools

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Domenico Talia
Keyword(s):  
High Performance ◽  
Workflow Management ◽  
Large Data ◽  
Scientific Applications ◽  
Data Repositories ◽  
Workflow Systems ◽  
Simulation Techniques ◽  
Workflow System ◽  
Computing Platforms ◽  
High Level

The wide availability of high-performance computing systems, Grids and Clouds, allowed scientists and engineers to implement more and more complex applications to access and process large data repositories and run scientific experiments in silico on distributed computing platforms. Most of these applications are designed as workflows that include data analysis, scientific computation methods, and complex simulation techniques. Scientific applications require tools and high-level mechanisms for designing and executing complex workflows. For this reason, in the past years, many efforts have been devoted towards the development of distributed workflow management systems for scientific applications. This paper discusses basic concepts of scientific workflows and presents workflow system tools and frameworks used today for the implementation of application in science and engineering on high-performance computers and distributed systems. In particular, the paper reports on a selection of workflow systems largely used for solving scientific problems and discusses some open issues and research challenges in the area.

The way of value of Correlation of genomic DNA microsatellite loci and live weight of Chukchi reindeer

2020 ◽  
pp. 27-32
Author(s):  
V. Dodokhov ◽  
N. Pavlova ◽  
T. Rumyantseva ◽  
L. Kalashnikova
Keyword(s):  
Microsatellite Markers ◽  
Agricultural Production ◽  
Live Weight ◽  
Biodiversity Loss ◽  
Tribal Community ◽  
High Germination ◽  
Wide Range ◽  
The Mean ◽  
High Level ◽  
Dna Microsatellite

The article presents the genetic characteristic of the Chukchi reindeer breed. The object of the study was of the Chukchi reindeer. In recent years, the number of reindeer of the Chukchi breed has declined sharply. Reduced reindeer numbers could lead to biodiversity loss. The Chukchi breed of deer has good meat qualities, has high germination viability and is adapted in adverse tundra conditions of Yakutia. Herding of the Chukchi breed of deer in Yakutia are engaged only in the Nizhnekolymsky district. There are four generic communities and the largest of which is the agricultural production cooperative of nomadic tribal community «Turvaurgin», which was chosen to assess the genetic processes of breed using microsatellite markers: Rt6, BMS1788, Rt 30, Rt1, Rt9, FCB193, Rt7, BMS745, C 143, Rt24, OheQ, C217, C32, NVHRT16, T40, C276. It was found that microsatellite markers have a wide range of alleles and generally have a high informative value for identifying of genetic differences between animals and groups of animal. The number of identified alleles is one of the indicators of the genetic diversity of the population. The total number of detected alleles was 127. The Chukchi breed of deer is characterized by a high level of heterozygosity, and the random crossing system prevails over inbreeding in the population. On average, there were 7.9 alleles (Na) per locus, and the mean number of effective alleles (Ne) was 4.1. The index of fixation averaged 0.001. The polymorphism index (PIC) ranged from 0.217 to 0.946, with an average of 0.695.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

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