SUSTAINABILITY PROJECT: RISK ANALYSIS BASED ON DECISION TREES UNDER CONDITIONS OF TOTAL AND PARTIAL IGNORANCE

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F16%3APU118549" target="_blank" >RIV/00216305:26510/16:PU118549 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.lka.lt/lt/moksline-veikla/leidiniai/journal-of-security-sak9/journal-of-security-krna.html" target="_blank" >http://www.lka.lt/lt/moksline-veikla/leidiniai/journal-of-security-sak9/journal-of-security-krna.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.9770/jssi.2015.5.3" target="_blank" >10.9770/jssi.2015.5.3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

SUSTAINABILITY PROJECT: RISK ANALYSIS BASED ON DECISION TREES UNDER CONDITIONS OF TOTAL AND PARTIAL IGNORANCE

Popis výsledku v původním jazyce

Sustainability project is an important part of project management and depends on many factors, such as financial resources, human resources, scheduling operations and especially potential risks. This paper presents a way to work with uncertain information processing project risk analysis with regard to its sustainability. Risk management is an important part of various disciplines, e.g. Project management, Crisis management, Change management, Information Security Management System, etc. Risk analysis is mostly based on expert estimates. However, this may be a problem with brand new tasks as identification of different threats and their numerical evaluations can be interpreted as a decision-making task which can be formalised as a decision tree. A decision-making task solution requires knowledge of all relevant input information items (III), such as probabilities, penalties and profits. If all those numerical values are known then the well-known methods of decision trees evaluations can be used. However, if complex project management problems are solved then a substantial set of relevant data items is missing or its accuracies are prohibitively low. The aim of this paper is to present easy approach how missing elements of the III set can be obtained and integrated into incomplete data sets. The paper contributes a common sense heuristics to obtain missing elements of the III set which can generate all numerical values, i.e. a problem under complete ignorance is solve, and a reconciliation mechanism based on linear programming which allows results of common sense heuristics simply integrate into incomplete data set, i.e. a problem under partial ignorance is solved. The results are therefore divided into two parts. In the first part solves a problem under total ignorance. The second part of the case study evaluates some unknown probabilities, therefore solves a problem under partial ignorance. Both tasks, i.e. partial and total ignorance are demonstrated using a quasi

Název v anglickém jazyce

SUSTAINABILITY PROJECT: RISK ANALYSIS BASED ON DECISION TREES UNDER CONDITIONS OF TOTAL AND PARTIAL IGNORANCE

Popis výsledku anglicky

Sustainability project is an important part of project management and depends on many factors, such as financial resources, human resources, scheduling operations and especially potential risks. This paper presents a way to work with uncertain information processing project risk analysis with regard to its sustainability. Risk management is an important part of various disciplines, e.g. Project management, Crisis management, Change management, Information Security Management System, etc. Risk analysis is mostly based on expert estimates. However, this may be a problem with brand new tasks as identification of different threats and their numerical evaluations can be interpreted as a decision-making task which can be formalised as a decision tree. A decision-making task solution requires knowledge of all relevant input information items (III), such as probabilities, penalties and profits. If all those numerical values are known then the well-known methods of decision trees evaluations can be used. However, if complex project management problems are solved then a substantial set of relevant data items is missing or its accuracies are prohibitively low. The aim of this paper is to present easy approach how missing elements of the III set can be obtained and integrated into incomplete data sets. The paper contributes a common sense heuristics to obtain missing elements of the III set which can generate all numerical values, i.e. a problem under complete ignorance is solve, and a reconciliation mechanism based on linear programming which allows results of common sense heuristics simply integrate into incomplete data set, i.e. a problem under partial ignorance is solved. The results are therefore divided into two parts. In the first part solves a problem under total ignorance. The second part of the case study evaluates some unknown probabilities, therefore solves a problem under partial ignorance. Both tasks, i.e. partial and total ignorance are demonstrated using a quasi

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50602 - Public administration

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Security and Sustainability Issues

ISSN

2029-7025

e-ISSN

—

Svazek periodika

5

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

LT - Litevská republika

Počet stran výsledku

11

Strana od-do

391-402

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84994477355