PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2020 | 11 | nr 4 | 81--91
Tytuł artykułu

Project Prioritizing in a Manufacturing - Service Enterprise with Application of the Fuzzy Logic

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article includes presentation of fuzzy numbers application in projects prioritizing at manufacturing and service providing enterprises. The following criteria have been applied as a basis for projects prioritizing analysis in enterprise: NPV index, linked with the enterprise strategic aims, project execution cost, project time, project scope and risk. As the criteria selected were of measurable and non-measurable character in projects prioritizing evaluation, the fuzzy decision making system has been developed, in which a linguistic value has been defined for each criterion of projects prioritizing. Knowledge base has been developed afterwards, presenting cause-effect dependencies in projects prioritizing. Knowledge base consisted of conditional rules. Fuzzy system of decision making in project prioritizing has been developed in MATLAB application. The decision making fuzzy system established, constitutes an efficient tool for projects prioritizing, on the basis of criteria given and concluding system developed. The obtained analysis results provide basis for the decision making parties to set the projects execution sequences. (original abstract)
Rocznik
Tom
11
Numer
Strony
81--91
Opis fizyczny
Twórcy
  • Opole University of Technology, Poland
  • Opole University of Technology, Poland
Bibliografia
  • PMI, A guide to the project management body of knowledge, 5th edition, Newtown Square, PA, USA: PMI, 2013.
  • Dobson M.S., Dobson D.S., Managing Multiple Projects, AMACOM American Management Association, New York, 2002.
  • Lova A., Maroto C., Tormos P., A multicriteria heuristic method to improve resource allocation in multiproject scheduling, European Journal of Operational Research, 127, 408-424, 2000.
  • Hass K.B., Introducing the new project complexity model part I, retrieved 16.01.2018, from: www.projecttimes.com, 2008.
  • Purnusa A., Bodeab C-N., Project Prioritization and Portfolio Performance Measurement in Project Oriented Organizations, Procedia - Social and Behavioral Sciences, 119, 339-348, 2014.
  • Vargas R.V., Using the analytic hierarchy process (AHP) to select and prioritize projects in a portfolio, retrieved 13.01.2018, from: https://www.pmi.org/ learning/library/analytic-hierarchy-process-prioritize- projects-6608, 2010.
  • Bojana Jovanovic B., Filipovic J., Bakic V., Prioritization of manufacturing sectors in Serbia for energy management improvement - AHP method, Energy Conversion and Management, 98, 225-235, 2015.
  • Chatterjee K., Hossain S.A., Kar S., Prioritization of project proposals in portfolio management using fuzzy AHP, Opserch, 55, 478-501, 2018.
  • Lee J.W., Kim S.H., An integrated approach for interdependent information system project selection, International Journal of Project Management, 19, 2, 111-118, 2001.
  • Meade L.M., Presley A., R&D Project Selection Using the Analytic Network Process, IEEE Transactions on Engineering Management, 49, 1, 59-66, 2002.
  • Oktavera R., Saraswati R., Framework for implementation project portfolio selection decision in a shipping company, Academic Research International, 3, 3, 163-174, 2012.
  • Peçanha De Souza L., Gomes C. F. S., Pinheiro De Barros A., Implementation of New Hybrid AHP - TOPSIS-2N Method in Sorting and Prioritizing of an it CAPEX Project Portfolio, International Journal of Information Technology & Decision Making, 17, 4, 977-1005, 2018.
  • Rabbani M., Tavakkoli-Moghaddam R., Jolai F., Ghorbani H.R., A Comprehensive Model for R and D project portfolio selection with zero-one linear goal-programming, IJE Transactions A: Basics, 19, 1, 55-66, 2006.
  • Sowlati T., Paradi J. C., Suld S., Information systems project prioritization using data envelopment analysis, Mathematical and Computer Modeling, 41, 1279-1298, 2005.
  • Shaygan A., Testik Ö. M., A fuzzy AHP-based methodology for project prioritization and selection, Soft Computer, 23, 1309-1319, 2019.
  • Tahere Y., Prioritizing key success factors of software projects using fuzzy AHP, Journal of Software Evolution and Process, 30, 1, 1-11, 2018.
  • Archer N.P., Ghasemzadeh F., An integrated framework for project portfolio selection, International Journal of Project Management, 17, 4, 207-216, 1999.
  • Bhaskar S.V., Megharaj B.R., An evaluation of project portfolio selection techniques in IT firms, Asia Pacific Journal of Research in Business Management, 2, 11, 183-191, 2001.
  • Denbo A., Guthrie R., Prioritizing IT Projects: An Empirical Application of an IT Investment Model, Communication of the IIMA, 3, 2, 135-142, 2003.
  • Barbati M., Figueira J.R., Greco S., Ishizaka A., Panaro S., A Multiple Criteria Methodology for Prioritizing and Selecting Portfolios of Urban Projects (13.12.2018), http://arxiv.org/pdf/1812.10410v2.
  • Ghasemzadeh F., Archer N.P., Project portfolio selection through decision support, Decision Support Systems, 29, 1, 73-88, 2000.
  • Purnus A., Bodea C-N., Project Prioritization and Portfolio oriented Organizations, Procedia-Social and Behavioral Sciences, 119, 339-348, 2014.
  • Aglan F., Lawrence A-F., Prioritizing process improvement initiatives in manufacturing environments, International Journal of Production Economics, 196, 261-268, 2018.
  • Santhanam R., Kyparisis G., A decision model for interdependent information system project selection, European Journal of Operational Research, 89, 2, 380-399, 1996.
  • Machacha L.L., Bahattacharya P., A fuzzy-logicbased approach to project selection, IEEE Transactions on Engineering Management, 47, 1, 65-73, 2000.
  • Zadeh L.A., The concept of a linguistic variable and its application to approximate reasoning, Information Sciences, 1, 3, 199-249, 1975.
  • Lelli S., Factor Analysis vs. Fuzzy Sets Theory: Assessing The Influence Of Different Techniques On Sen's Functioning Approach, Center of Economic Studies Discussion Paper, KU Leuven, DPS 01.21, pp. 1-35, 2001.
  • Peterson M.P., Interactive and Animated Cartography, Englewood Cliffs, Prentice-Hall, 1995.
  • Belohlavek R., Dauben J.W., Klir G.J., Fuzzy Logic and Mathematics: A Historical Perspective, Oxford, New York, 2017.
  • Mendel J.M., Uncertain Rule-Based Fuzzy-Systems, Interaduction and New Directions, Second Edition, Springer, USA, 2017.
  • Phyo A., Return on Design: Smarter Web Design That Works, New Riders Publishing, 2003.
  • Zimmerman H.J., Fuzzy set theory, WIREs Computational Statistics, 2, 3, 317-332, 2010.
  • Alem S.M., Jolai F., Shirkouhi A.N., An integrated fuzzy DEA-fuzzy AHP approach: A new model for ranking decision-making units, International Journal of Operational Research, 17, 1, 38-58, 2013.
  • Campuzano F., Mula J., Peidro D., Fuzzy estimations and system dynamics for improving supply chains, Fuzzy Sets and Systems, 161, 11, 1530-1542, 2010.
  • Gougam F., Rahmoune Ch., Benazzouz D., Merainani B., Bearing fault diagnosis based on feature extraction of empirical wavelet transform (EWT) and fuzzy logic system (FLS) under variable operating conditions, Journal of Vibroengineering, 21, 6, 1636-1650, 2019.
  • Gougam F., Rahmoune Ch., Benazzouz D., Afia A., Zair M., Bearing faults classification under various operation modes using time domain features, singular value decomposition, and fuzzy logic system, Advances in Mechanical Engineering, 12, 10, 1-17, 2020.
  • Kusar H., Aytekir O., Özdemir I., The use of fuzzy logic in predicting house selling price, Expert Systems with Applications, 37, 3, 1808-1813, 2010.
  • Mamadani E.H., Assilian S., An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man - Machine Studies, 7, 1, 1-13, 1975.
  • Medynskaya M.K., Fuzzy set theory, The concept of fuzzy sets, Soft Computing and Measurements (SCM) 2015 XVIII International Conference on Soft Computing and Measurements, pp. 30-31, 2015.
  • Robinson V.B., A Perspective on the Fundamentals of Fuzzy Sets and their Use in Geographic Information Systems, Transactions in GIS, 7, 1, 3-30, 2003.
  • Roubens M., Fuzzy sets and decision analysis, Fuzzy Sets and Systems, 90, 2, 199-206, 1997.
  • Teng J.Y., Tzeng G.H., Transportation investment project selection using fuzzy multiobjective programming, Fuzzy Sets and Systems, 96, 3, 259-280, 1998.
  • Yang H., Anumba C.J., Kamara J., Carrillo P., A fuzzy-based analytic approach to collaborative decision making for construction teams, Logistics Information Management, 14, 5/6, 344-355, 2001.
  • Zopounidis C., Pardalos P.M., Baourakis G., Fuzzy Sets in Management. Economics and Marketing, World Scientific Publishing: London, 2001.
  • Mamdani E.H., Applications of fuzzy algorithm for control a simple dynamic plant, Proceedings of the Institution of Electrical Engineers, 121, 12, 1585- 1588, 1974.
  • Dweir F.T., Kablan M.M., Using fuzzy decision making for the evaluation of the project management internal efficiency, Decision Support Systems, 42, 2, 712-726, 2006.
  • Zadeh L.A., Fuzzy sets, Computer, 21, 40, 83-93, 1988.
  • Zadeh L.A., Fu K.S., Tanaka K., Shimura M., Fuzzy sets and Their Applications to Cognitive and Decision Processes, Academic Press: London, 1975.
  • Błaszczyk K., Pisz I., Fuzzy decision-making system in the final evaluation of the project [in Polish: Rozmyty system podejmowania decyzji w ocenie koncowej projektu], Knosala R. [Ed.], T. 1, Oficyna Wydawnicza Polskiego Towarzystwo Zarzadzania Produkcja, Opole, 2010.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171610041

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.