eprintid: 8324
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/83/24
datestamp: 2023-11-09 16:20:13
lastmod: 2023-11-09 16:20:13
status_changed: 2023-11-09 16:12:22
type: article
metadata_visibility: show
creators_name: Balogun, A.-L.
creators_name: Matori, A.-N.
creators_name: Hamid-Mosaku, A.I.
creators_name: Umar Lawal, D.
creators_name: Ahmed Chandio, I.
title: Fuzzy MCDM-based GIS model for subsea oil pipeline route optimization: An integrated approach
ispublished: pub
keywords: Argon; Artificial intelligence; Computer circuits; Decision making; Decision support systems; Fuzzy logic; Geographic information systems; Geological surveys; Membership functions; Offshore petroleum prospecting; Petroleum pipelines; Petroleum transportation; Pipelines, Fuzzy linguistic variable; Hybrid decision support systems; MCDM; Multi-criteria decision making; Pipeline routing; SDSS; Spatial decision support systems; subsea, Transportation routes, fuzzy mathematics; GIS; integrated approach; multicriteria analysis; oil pipeline; optimization; routing; subsea production system, Malaysia
note: cited By 29
abstract: Proper pipeline route selection is an integral component of a typical oil exploration and transportation project. Improperly selected routes could have severe consequences including pipe failures, oil spillage, and environmental disasters. Consequently, technologies like geographic information systems (GIS) are increasingly being used to facilitate the oil pipeline route selection procedure�especially for onshore routing projects. Surprisingly, not much has been documented on the application of GIS to offshore pipeline routing. With recent discoveries on the merits of offshore oil exploration, it is necessary to extend the analytical capabilities of GIS to the unique offshore domain. However, concerns have been raised regarding the limitations of GIS in accurately prioritizing diverse selection criteria in typical multi-criteria decision-making (MCDM) problems like route selection. Consequently, this paper addresses the offshore/subsea pipeline routing constraint using a hybrid decision support system (DSS), which integrates a GIS and fuzzy logic-based approximate reasoning (AR) models for optimal performance. The resultant spatial decision support system (SDSS) was successfully applied to a case study in Malaysia. The AR algorithm calculated the significance level of the multiple criteria using various fuzzy linguistic variables and membership functions. The aggregated priority ranking from different pipeline routing experts showed that the overall influence of the environmental criteria (61.4) significantly exceeded that of other equally important criteria in the study area. These rankings were inputted into the SDSS to simulate various probable routes. Final results accurately highlighted an optimal route, which places a premium on the protection of environmental features in the subsea study area�in alignment with the preferences of majority of the experts. © 2017 Taylor & Francis.
date: 2017
publisher: Taylor and Francis Ltd.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010688277&doi=10.1080%2f1064119X.2016.1269247&partnerID=40&md5=ec0fe055fe5d84865af7e046470bd598
id_number: 10.1080/1064119X.2016.1269247
full_text_status: none
publication: Marine Georesources and Geotechnology
volume: 35
number: 7
pagerange: 961-969
refereed: TRUE
issn: 1064119X
citation:   Balogun, A.-L. and Matori, A.-N. and Hamid-Mosaku, A.I. and Umar Lawal, D. and Ahmed Chandio, I.  (2017) Fuzzy MCDM-based GIS model for subsea oil pipeline route optimization: An integrated approach.  Marine Georesources and Geotechnology, 35 (7).  pp. 961-969.  ISSN 1064119X