A hybrid fuzzy stochastic analytical hierarchy process FSAHP approach for evaluating ballast water treatment technologiesReport as inadecuate

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Environmental Systems Research

, 2:10

First Online: 09 November 2013Received: 27 August 2013Accepted: 04 November 2013


BackgroundEnvironmental decisions can be complex because of the inherent trade-offs among environmental, social, ecological, and economic factors. This paper presents a novel hybrid fuzzy stochastic analytical hierarchy process FSAHP approach to aid decision making by incorporating fuzzy and stochastic uncertainty into the traditional analytic hierarchy process AHP. A case study related to ballast water management is used to demonstrate the applicability of the proposed approach. Nine experts from government ministries and academic institutions are invited to evaluate five treatment technologies i.e., heat treatment, ultraviolet, ozone, ultrasound, and biocide based on a number of criteria such as efficacy, capital cost, and human risk.

ResultsThe experts’ preferences over the set of alternatives are represented as linguistic terms instead of numerical values. The beta-PERT distribution is adopted to approximate the probability density functions of the values of their inputs. Statistical analysis indicates that ultraviolet has the highest score 0.22–0.24 in most replications and its overlap with the second-best alternative is statistically negligible. Ozone, ultrasound, and heat treatment are mostly found as the second-, third-, and fourth-best alternatives with considerable overlaps that may be reduced if more experts are involved.

ConclusionsAs compared with the traditional AHP, the proposed FSAHP approach can not only take into account linguistic information but also capture the uncertainty associated with insufficient information and biased opinions in group decision-making problems.

KeywordsFSAHP approach Fuzzy Stochastic Ballast water management Group decision-making Electronic supplementary materialThe online version of this article doi:10.1186-2193-2697-2-10 contains supplementary material, which is available to authorized users.

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Author: Liang Jing - Bing Chen - Baiyu Zhang - Hongxuan Peng

Source: https://link.springer.com/

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