Guideline for MCDA Method Selection in Production Management Area

Each decision situation is described by a set of certain characteristics—a factor which classifies it into a category of decision problems. Many times the chosen problematic determines the choice of the most suitable Multi-Criteria Decision Analysis (MCDA) method to be employed for supporting a decision maker. The following paper deals with directions developing in the literature on choosing the MCDA method best suited to solve a given decision problem. In the study, two sources of factors which influence the choice of the method were identified: a subject of the decision and a characteristic of dependencies in the problem description. When considering factors originating from the subject of the decision, the main focus is on case studies which support applying a particular method to a given problem. Dependencies between parameters describing a problem were analysed from the impact that the existence of various data sources has to them. The selected group of factors was consecutively generalised and its impact on the result of the decision support (using a collection of methods) was pointed out. The performed analysis constitutes the source of the strategy for choosing one method from the considered group of methods. Examples of applications in production management area are given.

[1]  Vincent Mousseau,et al.  Inferring an ELECTRE TRI Model from Assignment Examples , 1998, J. Glob. Optim..

[2]  Camille Salinesi,et al.  MCDM Techniques Selection Approaches: State of the Art , 2007, 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making.

[3]  Jiangjiang Wang,et al.  A fuzzy multi-criteria decision-making model for trigeneration system , 2008 .

[4]  C. Zopounidis,et al.  A Multicriteria Decision Aid Methodology for Sorting Decision Problems: The Case of Financial Distress , 1999 .

[5]  Vincent F. Yu,et al.  An integrated fuzzy multi-criteria approach for the performance evaluation of multiple manufacturing plants , 2010, Comput. Ind. Eng..

[6]  Alexander Moffett,et al.  Incorporating multiple criteria into the design of conservation area networks: a minireview with recommendations , 2006 .

[7]  Georgios Athanasopoulos,et al.  A decision support system for coating selection based on fuzzy logic and multi-criteria decision making , 2009, Expert Syst. Appl..

[8]  Marcin Paprzycki,et al.  Applying Saaty's Multicriterial Decision Making Approach in Grid Resource Management , 2014, BCI.

[9]  Rifat Gürcan Özdemir,et al.  A hybrid approach to concept selection through fuzzy analytic network process , 2009, Comput. Ind. Eng..

[10]  M. R. Abdi,et al.  Fuzzy multi-criteria decision model for evaluating reconfigurable machines , 2009 .

[11]  Jun Wu,et al.  Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process , 2007 .

[12]  Te-Sheng Li,et al.  Applying TRIZ and Fuzzy AHP to develop innovative design for automated manufacturing systems , 2009, Expert Syst. Appl..

[13]  Simon French,et al.  A manifesto for the new MCDA era , 1993 .

[14]  Serge Kokot,et al.  Selection of hydrothermal pre-treatment conditions of waste sludge destruction using multicriteria decision-making. , 2005, Journal of environmental management.

[15]  Jaap Spronk,et al.  Multicriteria Decision Aid/Analysis in Finance , 2005 .

[16]  Mohamed Marzouk,et al.  ELECTRE III Model for Value Engineering Applications. , 2011 .

[17]  Carlos A. Bana e Costa,et al.  On the Mathematical Foundation of MACBETH , 2005 .

[18]  Adel Guitouni,et al.  Tentative guidelines to help choosing an appropriate MCDA method , 1998, Eur. J. Oper. Res..

[19]  Irfan Ertugrul,et al.  Fuzzy Multi-criteria Decision Making Method for Machine Selection , 2007, Analysis and Design of Intelligent Systems using Soft Computing Techniques.

[20]  María Teresa Lamata,et al.  Selection of a cleaning system for engine maintenance based on the analytic hierarchy process , 2009, Comput. Ind. Eng..

[21]  Yan Li,et al.  A Multiple Criteria Decision Analysis (MCDA) Software Selection Framework , 2014, 2014 47th Hawaii International Conference on System Sciences.

[22]  Fausto Cavallaro,et al.  A comparative assessment of thin-film photovoltaic production processes using the ELECTRE III method , 2010 .

[23]  Thomas L. Saaty,et al.  The Analytic Hierarchy and Analytic Network Processes for the Measurement of Intangible Criteria and for Decision-Making , 2016 .

[24]  E. Triantaphyllou,et al.  Ranking irregularities when evaluating alternatives by using some ELECTRE methods , 2008 .

[25]  T. Saaty How to Make a Decision: The Analytic Hierarchy Process , 1990 .

[26]  James S. Dyer,et al.  Maut — Multiattribute Utility Theory , 2005 .

[27]  Thierry Marchant,et al.  Evaluation and Decision Models with Multiple Criteria: Stepping Stones for the Analyst , 2006 .

[28]  Ali Shanian,et al.  A material selection model based on the concept of multiple attribute decision making , 2006 .

[29]  Haihong Huang,et al.  Multi-criteria decision making and uncertainty analysis for materials selection in environmentally conscious design , 2011 .

[30]  R. C. Abeyaratne,et al.  A new application of ELECTRE III and revised Simos' procedure for group material selection under weighting uncertainty , 2008, Knowl. Based Syst..

[31]  Zbigniew Piotrowski,et al.  The Selection of Multicriteria Method Based on Unstructured Decision Problem Description , 2014, ICCCI.

[32]  Philippe Fortemps,et al.  Multicriteria Choice and Ranking Using Decision Rules Induced from Rough Approximation of Graded Preference Relations , 2004, Rough Sets and Current Trends in Computing.

[33]  A. Shanian,et al.  A methodological concept for material selection of highly sensitive components based on multiple criteria decision analysis , 2009, Expert Syst. Appl..

[34]  Thomas Spengler,et al.  Fuzzy outranking for environmental assessment. Case study: iron and steel making industry , 2000, Fuzzy Sets Syst..

[35]  B. Roy THE OUTRANKING APPROACH AND THE FOUNDATIONS OF ELECTRE METHODS , 1991 .

[36]  Ivan Mihajlović,et al.  Multi-criteria ranking of copper concentrates according to their quality--an element of environmental management in the vicinity of copper--smelting complex in Bor, Serbia. , 2009, Journal of environmental management.

[37]  M. Yurdakul,et al.  Analysis of the benefit generated by using fuzzy numbers in a TOPSIS model developed for machine tool selection problems , 2009 .

[38]  João Paulo Davim,et al.  A decision-making framework model for material selection using a combined multiple attribute decision-making method , 2008 .

[39]  Ludmil Mikhailov,et al.  Fuzzy analytical approach to partnership selection in formation of virtual enterprises , 2002 .