Development of a rough set-based decision support system for life cycle impact assessment and interpretation

Life cycle assessment (LCA) is a methodological framework for assessing the environmental impacts of products or processes during their entire lifetime. It consists of four phases: (1) goal and scope definition, (2) inventory analysis (LCI), (3) impact assessment (LCIA) and (4) interpretation. LCA i...

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Main Author: Aviso, Kathleen B.
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Language:English
Published: Animo Repository 2006
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Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/3372
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_masteral-102102022-11-16T01:15:55Z Development of a rough set-based decision support system for life cycle impact assessment and interpretation Aviso, Kathleen B. Life cycle assessment (LCA) is a methodological framework for assessing the environmental impacts of products or processes during their entire lifetime. It consists of four phases: (1) goal and scope definition, (2) inventory analysis (LCI), (3) impact assessment (LCIA) and (4) interpretation. LCA involves the simultaneous evaluation of multiple criteria or multiple goals. A systematic way of dealing with this problem is provided by Decision Analysis techniques, particularly through the use of multiple criteria decision analysis (MCDA) methods. MCDA methods include the multi-attribute utility/value theory (MAUT/MAVT), outranking methods and the analytical hierarchy process (AHP). Thus recognizing the benefits, most of the existing LCIA and interpretation methods patterned their frameworks to MCDA methods. However, these require decision makers (DM) to express their preferences into importance weights or parameters, which are necessary for the chosen preference model - a task, which is tedious. Hence, an alternative approach is recommended in this study. The use of rough set methodology has been successfully applied to multiple criteria or multiple attribute problems in engineering, medicine, banking, economics, and financial and market analysis. It is capable of finding patterns in data and dealing with uncertainties and inconsistencies, which may be due to a DMs limited discriminatory power. It only requires previously expressed decisions made by the DM to infer the DMs adapted preference model in terms of decision rules. This study thus presents the development of a decision support system (DSS) utilizing a two-step procedure of Pareto optimality and rough set methodology for impact assessment and interpretation. This alternative methodology has shown comparability in results with AHP and was found to predict accurately the decisions of experts to a degree of 83%. The model, which is founded on the decision rules derived from the assessment of a panel of experts on a set of power generating technologies, encapsulates the environmental concerns considered and the state of knowledge of the experts during the time of the survey. Thus this model can be utilized to rank and evaluate new technologies against four other systems, which are stored in the models database, based on the same arguments utilized for assessing the training data examples. 2006-01-01T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etd_masteral/3372 Master's Theses English Animo Repository Decision support systems Rough sets Product life cycle--Environmental aspects Environmental Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Decision support systems
Rough sets
Product life cycle--Environmental aspects
Environmental Engineering
spellingShingle Decision support systems
Rough sets
Product life cycle--Environmental aspects
Environmental Engineering
Aviso, Kathleen B.
Development of a rough set-based decision support system for life cycle impact assessment and interpretation
description Life cycle assessment (LCA) is a methodological framework for assessing the environmental impacts of products or processes during their entire lifetime. It consists of four phases: (1) goal and scope definition, (2) inventory analysis (LCI), (3) impact assessment (LCIA) and (4) interpretation. LCA involves the simultaneous evaluation of multiple criteria or multiple goals. A systematic way of dealing with this problem is provided by Decision Analysis techniques, particularly through the use of multiple criteria decision analysis (MCDA) methods. MCDA methods include the multi-attribute utility/value theory (MAUT/MAVT), outranking methods and the analytical hierarchy process (AHP). Thus recognizing the benefits, most of the existing LCIA and interpretation methods patterned their frameworks to MCDA methods. However, these require decision makers (DM) to express their preferences into importance weights or parameters, which are necessary for the chosen preference model - a task, which is tedious. Hence, an alternative approach is recommended in this study. The use of rough set methodology has been successfully applied to multiple criteria or multiple attribute problems in engineering, medicine, banking, economics, and financial and market analysis. It is capable of finding patterns in data and dealing with uncertainties and inconsistencies, which may be due to a DMs limited discriminatory power. It only requires previously expressed decisions made by the DM to infer the DMs adapted preference model in terms of decision rules. This study thus presents the development of a decision support system (DSS) utilizing a two-step procedure of Pareto optimality and rough set methodology for impact assessment and interpretation. This alternative methodology has shown comparability in results with AHP and was found to predict accurately the decisions of experts to a degree of 83%. The model, which is founded on the decision rules derived from the assessment of a panel of experts on a set of power generating technologies, encapsulates the environmental concerns considered and the state of knowledge of the experts during the time of the survey. Thus this model can be utilized to rank and evaluate new technologies against four other systems, which are stored in the models database, based on the same arguments utilized for assessing the training data examples.
format text
author Aviso, Kathleen B.
author_facet Aviso, Kathleen B.
author_sort Aviso, Kathleen B.
title Development of a rough set-based decision support system for life cycle impact assessment and interpretation
title_short Development of a rough set-based decision support system for life cycle impact assessment and interpretation
title_full Development of a rough set-based decision support system for life cycle impact assessment and interpretation
title_fullStr Development of a rough set-based decision support system for life cycle impact assessment and interpretation
title_full_unstemmed Development of a rough set-based decision support system for life cycle impact assessment and interpretation
title_sort development of a rough set-based decision support system for life cycle impact assessment and interpretation
publisher Animo Repository
publishDate 2006
url https://animorepository.dlsu.edu.ph/etd_masteral/3372
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