Project Success Evaluation Model Based on FIS

Authors

  • Radek Doskočil Brno University of Technology, Faculty of Business and Management
  • Petr Dostál Brno University of Technology, Faculty of Business and Management

Keywords:

project management, decision-making, project success, fuzzy logic, soft computing

Abstract

Purpose of the article The article presents the expert fuzzy model for evalutation of project success. It is also verified and futher specified there. The fuzzy inference system (FIS) consists of three input variables one rule block and one output variable. The fuzzy inference system for evaluation of project success is presented in the form of a case study.

Methodology/methods Methods of analysis, synthesis and techniques of mathematical fuzzy modelling (fuzzy seets, fuzzy logic) were used to fulfil the aim. The Gaussian curve membership function (gaussmf) was used.

Scientific aim The aim of the article is to present an expert decision-making fuzzy model for evaluation of project success in the form of a case study.

Findings The reliable proposed expert decision-making fuzzy model consists three input variables (Project Status, Project Risk, Project Quality), one rule block (with 125 fuzzy rules) and one output variable (Project Succes). The inputs variables and output variable have five attributes (VL – very large, L – large, M – medium, S – small, VS – very small).

Conclusions The proposed fuzzy model is used as a tool for supprot of decision-making in project management. The project managers can systematically evaluate the basic project processes and the project success as a whole. They have the opportunity of using the fuzzy model for experimentation or simulations and they can relatively fast apply appropriate measures in project management. The proposed fuzzy model is recomended to use in the realisation phases of the project.

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Published

2017-10-01

Issue

2017: PROCEEDING OF SELECTED PAPERS

Section

System Engineering in Digital Transformation

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