Forming Set and Verification of Relevance Criteria on Evaluation of Alternative Corridors of the Infrastructure Facilities

Abstract Most of the models, which are already a small number, for selection of the optimal spatial solutions of the corridor of line infrastructure facilities are based on the criteria of evaluation whose relevance has not been verified. As a set of criteria is a starting basis for development of the hierarchical model of decision-making for the evaluation and selection of the optimum spatial solutions corridors, so is the relevance of the optimal solution of the selected model is based on selected criteria so much in question. This paper develops a model for the formation of a set of criteria of evaluation of alternative spatial solutions corridor of the line infrastructure facilities respectively their identification, derivation and grouping (clastering) and verification of their relevance. The model consists of two inter-related and complex steps. In the first step is formed a set of preliminary criteria of decision-making, in four also complex sub-steps. In the second step, with the help of statistical methods, such as surveys, descriptive statics and the most important, the factor analysis, verifies the relevance of each of the criteria from the preliminary set individually, and verifies (or does not verify) hierarchical model of decision-making, with the verification of its factors, formed on the basis of this set of criteria. In this way is obtained a finite set of relevant criteria of decision-making. The optimal solution selected through hierarchical model based on a set of relevant criteria has credible relevance .

[1]  Min Ouyang,et al.  Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis , 2015, Reliab. Eng. Syst. Saf..

[2]  Bijan Sarkar,et al.  A De Novo multi-approaches multi-criteria decision making technique with an application in performance evaluation of material handling device , 2015, Comput. Ind. Eng..

[3]  Majid Salari,et al.  A bi-level programming model for protection of hierarchical facilities under imminent attacks , 2015, Comput. Oper. Res..

[4]  Kirti Peniwati,et al.  Aggregating individual judgments and priorities with the analytic hierarchy process , 1998, Eur. J. Oper. Res..

[5]  Edmundas Kazimieras Zavadskas,et al.  Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014 , 2015, Expert Syst. Appl..

[6]  Costas Papadimitriou,et al.  Hierarchical Bayesian model updating for structural identification , 2015 .

[7]  Leslie M. Marx,et al.  Process Variation As a Determinant of Bank Performance: Evidence From the Retail Banking Study , 1999 .

[8]  A. Kashyap,et al.  Real estate market led land development strategies for regional economic corridors – A tale of two mega projects , 2015 .

[9]  Wei Xiong,et al.  A hierarchical model for label constraint reachability computation , 2015, Neurocomputing.

[10]  António Ramos Andrade,et al.  Statistical modelling of railway track geometry degradation using Hierarchical Bayesian models , 2015, Reliab. Eng. Syst. Saf..

[11]  Laure Criqui,et al.  Infrastructure urbanism: Roadmaps for servicing unplanned urbanisation in emerging cities , 2015 .

[12]  Bertrand Mareschal,et al.  Prométhée: a new family of outranking methods in multicriteria analysis , 1984 .

[13]  Alev Taskin Gumus,et al.  A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets , 2015, Knowl. Based Syst..