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P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives

Widespread adoption of bioenergy for electricity generation could lead to a globally greener environment, with significant climatic and waste management benefits. Numerous methodologies have been developed to optimize the performance of bioenergy supply chains with different objective functions (e.g...

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Main Authors:	Ng, Rex T.L., Tan, Raymond R., Hassim, Mimi Haryani
Format:	Conference or Workshop Item
Published:	2015
Subjects:	QE Geology
Online Access:	http://eprints.utm.my/id/eprint/61774/ http://www.conferencepres.com/Data/Sites/1/docs/PRES-2015.pdf
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id	my.utm.61774
record_format	eprints
spelling	my.utm.617742017-08-07T01:16:47Z http://eprints.utm.my/id/eprint/61774/ P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives Ng, Rex T.L. Tan, Raymond R. Hassim, Mimi Haryani QE Geology Widespread adoption of bioenergy for electricity generation could lead to a globally greener environment, with significant climatic and waste management benefits. Numerous methodologies have been developed to optimize the performance of bioenergy supply chains with different objective functions (e.g., profitability, carbon footprint, etc.) usually based on conventional optimization techniques. Such techniques are usually based on single-objective formulations, and are able to determine unique optimal solutions. Process graph (P-graph) is a graph-theoretic methodology which has been applied towards various network optimization problems in different domains. It offers advantages of computational efficiency for large-scale combinatorial problems, as well as the capability to identify both optimal and near-optimal solutions; the latter feature is especially good for decision-makers in practical applications. This paper presents an approach to the planning of bioenergy supply chains, taking into account both total cost minimization and supply chain risk reduction. The supply chain risk is accounted for in terms of transportation fatalities computed in an actuarial manner. An illustrative example based on Malaysian palm-based bioenergy supply chain is solved to illustrate the proposed approach. 2015 Conference or Workshop Item PeerReviewed Ng, Rex T.L. and Tan, Raymond R. and Hassim, Mimi Haryani (2015) P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives. In: Modelling and Optimisation for Energy Saving and Pollution Reduction 2015 (PRES 2015), 22-27 Aug, 2015, Sarawak, Malaysia. http://www.conferencepres.com/Data/Sites/1/docs/PRES-2015.pdf
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	QE Geology
spellingShingle	QE Geology Ng, Rex T.L. Tan, Raymond R. Hassim, Mimi Haryani P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives
description	Widespread adoption of bioenergy for electricity generation could lead to a globally greener environment, with significant climatic and waste management benefits. Numerous methodologies have been developed to optimize the performance of bioenergy supply chains with different objective functions (e.g., profitability, carbon footprint, etc.) usually based on conventional optimization techniques. Such techniques are usually based on single-objective formulations, and are able to determine unique optimal solutions. Process graph (P-graph) is a graph-theoretic methodology which has been applied towards various network optimization problems in different domains. It offers advantages of computational efficiency for large-scale combinatorial problems, as well as the capability to identify both optimal and near-optimal solutions; the latter feature is especially good for decision-makers in practical applications. This paper presents an approach to the planning of bioenergy supply chains, taking into account both total cost minimization and supply chain risk reduction. The supply chain risk is accounted for in terms of transportation fatalities computed in an actuarial manner. An illustrative example based on Malaysian palm-based bioenergy supply chain is solved to illustrate the proposed approach.
format	Conference or Workshop Item
author	Ng, Rex T.L. Tan, Raymond R. Hassim, Mimi Haryani
author_facet	Ng, Rex T.L. Tan, Raymond R. Hassim, Mimi Haryani
author_sort	Ng, Rex T.L.
title	P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives
title_short	P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives
title_full	P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives
title_fullStr	P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives
title_full_unstemmed	P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives
title_sort	p-graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives
publishDate	2015
url	http://eprints.utm.my/id/eprint/61774/ http://www.conferencepres.com/Data/Sites/1/docs/PRES-2015.pdf
_version_	1643655257269469184
score	13.211869

P-Graph methodology for bi-objective optimization of bioenergy supply chains: economic and safety perspectives

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