A framework for optimal rank identification of resource management systems using probabilistic approaches in analytic hierarchy process

Author:

Gorripati Ravi1ORCID,Thakur Mainak1,Kolagani Nagesh2

Affiliation:

1. a Indian Institute of Information Technology Sri City, Chittoor, Andhra Pradesh, India

2. b Centurion University of Technology and Management, Odisha, India

Abstract

Abstract A resource management system is likely to succeed if stakeholders get involved in analyzing and choosing from the alternatives. The present work deals with multi-criteria decision models to evaluate rain water harvesting (RWH) structures. Standard practice is to acquire the weights for criteria from stakeholders using analytic hierarchy process (AHP) to predict the RWH structures' performance and rank them. Challenges in this process are that the data collection is laborious and time-consuming, considers limited stakeholders' opinions, and suffers from lower confidence factors. This work proposes a probabilistic approach to AHP using Monte Carlo simulation (MCS) to model uncertainty. The proposal is to collect multiple assessments instead of a single judgment from knowledgeable stakeholders (KSH) with customized questionnaires and to compute the relative importance of criteria using pairwise comparisons. Stochastically similar assessments within the range of these samples are then generated using different distribution functions to compute the performance of the RWH structures. The computed performance correlated well with common stakeholders' (CSH) opinions in the case study involving 10 existing RWH structures with seven different criteria, for all the distributions. The mean relative error with the proposed method is approximately 21% less than the existing point estimate method.

Publisher

IWA Publishing

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development

Reference38 articles.

1. An integrated fuzzy QFD and TOPSIS methodology for choosing the ideal gas fuel at WWTPs;Energy,2017

2. Failure analysis of a partially collapsed building using analytical hierarchical process;Journal of Failure Analysis and Prevention,2020

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