title: A fuzzy analytic network process for multi-criteria evaluation of contaminated site remedial countermeasures.
abstract: The Analytic Network Process (ANP) has been proposed to incorporate interdependence and feedback effect in the prioritization of remedial countermeasures using a hierarchical network decision model, but this approach seems to be incapable of capturing the vagueness and fuzziness during value judgment elicitation. The aim of this paper is to present an evaluation method using a fuzzy ANP (FANP) approach to address this shortcoming. Triangular fuzzy numbers (TFN) and their degree of fuzziness are used in the semantic scale as human judgment expressed in natural language is most often vague and fuzzy. The method employs the alpha-cuts, interval arithmetic and optimism index to transform the fuzzy comparative judgment matrix into set of crisp matrices, and then calculates the desired priorities using the eigenvector method. A numerical example, which was drawn from a real-life case study of an uncontrolled landfill in Japan, is presented to demonstrate the process. Results from the sensitivity analysis describe how the fuzziness in judgment could affect the solution robustness of the prioritization method. The proposed FANP approach therefore could effectively deal with the uncertain judgment inherent in the decision making process and derive the meaningful priorities explicitly from a complex decision structure in the evaluation of contaminated site remedial countermeasures.
authors.affiliation: Laboratory of Sound Material-Cycle Systems Planning, Graduate School of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo 060-8628, Hokkaido, Japan. mpromentilla@yahoo.com
authors.forename: Michael Angelo B
authors.initials: MA
authors.lastname: Promentilla
authors.forename: T
authors.initials: T
authors.lastname: Furuichi
authors.forename: K
authors.initials: K
authors.lastname: Ishii
authors.forename: N
authors.initials: N
authors.lastname: Tanikawa
mesh_terms: D000465:Algorithms; D052918:Environmental Restoration and Remediation; D017143:Fuzzy Logic