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FMMSIC: a hybrid fuzzy based decision support system for MMS (in order to estimate interrelationships between criteria) / F. Samimi Namin in Journal of the operational research society (JORS), Vol. 63 N° 2 (Fevrier 2012) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 63 N° 2 (Fevrier 2012) . - pp. 218–231 Titre : FMMSIC: a hybrid fuzzy based decision support system for MMS (in order to estimate interrelationships between criteria) Type de document : texte imprimé Auteurs : F. Samimi Namin, Auteur ; K. Shahriar, Auteur ; A. Bascetin, Auteur Année de publication : 2012 Article en page(s) : pp. 218–231 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Hybrid  decision  support  system  Fuzzy  entropy  Fuzzy  ANP  Modified  TOPSIS  Mining  method  selection  FMMSIC Index. décimale : 001.424 Résumé : One of the main tasks in exploitation of ore-body is to select a suitable mining method. In mining method selection (MMS) problems, a decision procedure has to choose the best exploitation method that satisfies the evaluation criteria. It is generally hard to find a mining method that meets all the criteria simultaneously, therefore a good compromise solution is preferred as the final selection. Furthermore, the MMS problem is an inherently uncertain activity. To deal with the uncertainty, this paper presents an hybrid decision support system based on the fuzzy multi attribute decision making, named the fuzzy mining method selection with interrelation criteria (FMMSIC). FMMSIC models the relative weights of criteria by combining the fuzzy analytic network process and fuzzy entropy, and discusses using these hybrid techniques to determine the overall weights. Subsequently, the technique for order preference by similarity to an ideal solution method was modified by various normalization norms according to the MMS problem condition. Finally, to illustrate how the FMMSIC is used for the MMS problems, an empirical study of a real case is conducted. It shows by means of an application that the FMMSIC is well suited as a decision support system for the MMS. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n2/abs/jors201124a.html [article] FMMSIC: a hybrid fuzzy based decision support system for MMS (in order to estimate interrelationships between criteria) [texte imprimé] / F. Samimi Namin, Auteur ; K. Shahriar, Auteur ; A. Bascetin, Auteur . - 2012 . - pp. 218–231. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 63 N° 2 (Fevrier 2012) . - pp. 218–231 Mots-clés : Hybrid  decision  support  system  Fuzzy  entropy  Fuzzy  ANP  Modified  TOPSIS  Mining  method  selection  FMMSIC Index. décimale : 001.424 Résumé : One of the main tasks in exploitation of ore-body is to select a suitable mining method. In mining method selection (MMS) problems, a decision procedure has to choose the best exploitation method that satisfies the evaluation criteria. It is generally hard to find a mining method that meets all the criteria simultaneously, therefore a good compromise solution is preferred as the final selection. Furthermore, the MMS problem is an inherently uncertain activity. To deal with the uncertainty, this paper presents an hybrid decision support system based on the fuzzy multi attribute decision making, named the fuzzy mining method selection with interrelation criteria (FMMSIC). FMMSIC models the relative weights of criteria by combining the fuzzy analytic network process and fuzzy entropy, and discusses using these hybrid techniques to determine the overall weights. Subsequently, the technique for order preference by similarity to an ideal solution method was modified by various normalization norms according to the MMS problem condition. Finally, to illustrate how the FMMSIC is used for the MMS problems, an empirical study of a real case is conducted. It shows by means of an application that the FMMSIC is well suited as a decision support system for the MMS. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n2/abs/jors201124a.html