Decision Making in Uncertain Rural Scenarios by means of Fuzzy TOPSIS Method

A great deal of uncertain information which is difficult to quantify is taken into account by farmers and experts in the enterprise when making decisions. We are interested in the problems of the implementation of a rabbit-breeding farm. One of the first decisions to be taken refers to the design or type of structure for housing the animals, which is determined by the level of environmental control sought to be maintained in its interior. A farmer was consulted, and his answers were incorporated into the analysis, by means of the fuzzy TOPSIS methodology. The main purpose of this paper is to study the problem by means of the fuzzy TOPSIS method as multicriteria decision making, when the information was given in linguistic terms.

[1]  Uzay Kaymak,et al.  Elicitation of expert knowledge for fuzzy evaluation of agricultural production systems , 2003 .

[2]  Jean-Marie Aerts,et al.  Original papers: Real-time recognition of sick pig cough sounds , 2008 .

[3]  Ken E. Giller,et al.  Manure as a key resource within smallholder farming systems: Analysing farm-scale nutrient cycling efficiencies with the NUANCES framework , 2007 .

[4]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[5]  Ronald R. Yager,et al.  An approach to ordinal decision making , 1995, Int. J. Approx. Reason..

[6]  T. Bogdanik [Use of fuzzy set theory in diagnostics]. , 1995, Polskie Archiwum Medycyny Wewnetrznej.

[7]  María Teresa Lamata,et al.  Multi-criteria analysis for a maintenance management problem in an engine factory: rational choice , 2011, J. Intell. Manuf..

[8]  Chen-Tung Chen,et al.  A New Decision-Making Method for Stock Portfolio Selection Based on Computing with Linguistic Assessment , 2009, Adv. Decis. Sci..

[9]  Alberto Tellaeche,et al.  A new vision-based approach to differential spraying in precision agriculture , 2008 .

[10]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[11]  M. S. García-Cascales,et al.  Decision support in disinfection technologies for treated wastewater reuse , 2009 .

[12]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[13]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[14]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[15]  Walter A.H. Rossing,et al.  Integrative modelling approaches for analysis of impact of multifunctional agriculture: A review for France, Germany and The Netherlands , 2007 .

[16]  Manuel Arriaza,et al.  Spatial analysis of the suitability of olive plantations for wildlife habitat restoration , 2009 .

[17]  María Teresa Lamata,et al.  A Modification of the Index of Liou and Wang for Ranking Fuzzy Number , 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[18]  Janusz Kacprzyk,et al.  Computing with Words in Information/Intelligent Systems 1 , 1999 .

[19]  R. Yager A NEW METHODOLOGY FOR ORDINAL MULTIOBJECTIVE DECISIONS BASED ON FUZZY SETS , 1993 .

[20]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[21]  C. Hwang,et al.  TOPSIS for MODM , 1994 .

[22]  Da Ruan,et al.  Multi-Objective Group Decision Making - Methods, Software and Applications with Fuzzy Set Techniques(With CD-ROM) , 2007, Series in Electrical and Computer Engineering.

[23]  Andrew P. Whitmore,et al.  Is it possible to increase the sustainability of arable and ruminant agriculture by reducing inputs , 2009 .

[24]  Madan M. Gupta,et al.  Approximate reasoning in decision analysis , 1982 .

[25]  Jiaguo Qi,et al.  Comparison of BRDF models with a fuzzy inference system for correction of bidirectional effects , 2003 .

[26]  Marc Roubens,et al.  Multiple criteria decision making , 1994 .

[27]  Oscar Castillo,et al.  Analysis and Design of Intelligent Systems Using Soft Computing Techniques , 2007 .

[28]  Francisco Herrera,et al.  Computing with Words in Decision support Systems: An overview on Models and Applications , 2010, Int. J. Comput. Intell. Syst..

[29]  María Teresa Lamata,et al.  PC-TOPSIS Method for the Selection of a Cleaning System for Engine Maintenance , 2007, Analysis and Design of Intelligent Systems using Soft Computing Techniques.

[30]  Janusz Kacprzyk,et al.  LINGUISTIC SUMMARIES OF DATA USING FUZZY LOGIC , 2001 .

[31]  Ronald R. Yager,et al.  Non-numeric multi-criteria multi-person decision making , 1993 .

[32]  Jacques Wery,et al.  SIMBA, a model for designing sustainable banana-based cropping systems , 2008 .

[33]  R. Yager Concepts, Theory, and Techniques A NEW METHODOLOGY FOR ORDINAL MULTIOBJECTIVE DECISIONS BASED ON FUZZY SETS , 1981 .

[34]  Romy Greiner,et al.  Motivations, risk perceptions and adoption of conservation practices by farmers , 2009 .

[35]  J. Quinn,et al.  Transformation toward agricultural sustainability in New Zealand hill country pastoral landscapes , 2008 .

[36]  Nick Evans,et al.  Adjustment strategies revisited: Agricultural change in the Welsh Marches , 2009 .