Combined Life Cycle Assessment and Costing Analysis Optimization Model Using Multiple Criteria Decision Making in Earth-Resource Systems
Affiliation(s)
Department of Energy and Mineral Engineering, Penn State University, University Park, USA.
Department of Energy and Mineral Engineering, Penn State University, University Park, USA.
ABSTRACT
Life Cycle Assessment (LCA) is a comprehensive method to evaluate all
attributes or aspects of potential environmental impact throughout a product’s
lifecycle. Financial impacts are often added to the systemic evaluation process
to reflect both environmental and economic assessment. For the specific
application of LCA informing design of new technologies, when numerous
variables are undecided or under defined, the process of forming an inventory of
complete dataset is very difficult. Accumulating the early data consumes time,
and limits application of LCA to new technologies and projects. As such, LCA
may not normally be associated with forecasting or guiding a design/production
process with an incomplete data set. Here, a life cycle assessment optimization
model (LCAO) is described for incomplete data sets, based on the life cycle
inventory (LCI) hybrid method and a modified multiple criteria decision making
(MCDM) approach. The approach requires data, but can proceed in the given an
incomplete or uncertain data set. The model of the algorithm also shows
promising results to reveal previously unknown key variables within the dataset,
which can then facilitate the minimization of environmental impact while
maximizing economic benefits in product design.
Cite this paper
Nieto, A. , Bai, Y. and Brownson, J. (2014) Combined Life Cycle Assessment and Costing Analysis Optimization Model Using Multiple Criteria Decision Making in Earth-Resource Systems. Natural Resources, 5, 351-358. doi: 10.4236/nr.2014.58033.
Nieto, A. , Bai, Y. and Brownson, J. (2014) Combined Life Cycle Assessment and Costing Analysis Optimization Model Using Multiple Criteria Decision Making in Earth-Resource Systems. Natural Resources, 5, 351-358. doi: 10.4236/nr.2014.58033.
References
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http://dx.doi.org/10.1016/j.ecolecon.2003.10.013 [4] International Standard ISO 14040 (2006) Environmental Management—Life Cycle Assessment—Principle and Framework. [5] Dantzig, G.B. (1963) Linear Programming and Extensions. Princeton University Press, Princeton. [6] Floudas, C.A. (1995) Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications. University Press, Oxford. [7] Dash Associates (1993) XPRESS-MP, User Guide. Dash Associates Blisworth. [8] GAMS (1998) Software GmbH Giessen, Germany.
[1] Guinée, I.B., et al. (2005) Life Cycle Assessment, Kirk-Othmer Encyclopedia of Chemical Technology. John Wiley & Sons, Inc. [2] Hall, C., Cutler, C. and Kaufmann, R. (1992) Energy and Resource Quality. University Press of Colorado, Boulder. [3] Sangwon, S. (2004) Functions, Commodities and Environmental Impacts in an Ecological-Economic Model. Ecological Economics, 48, 451-467.
http://dx.doi.org/10.1016/j.ecolecon.2003.10.013 [4] International Standard ISO 14040 (2006) Environmental Management—Life Cycle Assessment—Principle and Framework. [5] Dantzig, G.B. (1963) Linear Programming and Extensions. Princeton University Press, Princeton. [6] Floudas, C.A. (1995) Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications. University Press, Oxford. [7] Dash Associates (1993) XPRESS-MP, User Guide. Dash Associates Blisworth. [8] GAMS (1998) Software GmbH Giessen, Germany.