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Concepts in Risk Assessment
Published in D. Kofi Asante-Duah, Hazardous Waste Risk Assessment, 2021
Decision analysis is a management tool that consists of a conceptual and systematic procedure for analyzing complex sets of alternatives in a rational manner so as to improve the overall performance of the decision-making process. Decision theory provides a logical and systematic framework to structure objectives and to evaluate and rank alternative potential solutions to a problem. Multiattribute decision analysis and utility theory have been suggested (e.g., Lifson, 1972; Keeney and Raiffa, 1976) for the evaluation of problems involving multiple conflicting objectives, such as is the case for decisions on hazardous waste management programs. Under such circumstances, the decision maker is faced with the problem of having to trade off the performance of one objective against another. A mathematical structure may be developed around utility theory that presents a deductive philosophy for risk-based decisions (Lifson, 1972; Keeney and Raiffa, 1976; Starr and Whipple, 1980; Keeney, 1984). It should be acknowledged that, although decision analysis presents a systematic and flexible technique that incorporates the decision makers’ judgment, it does not provide a complete analysis of the public’s perception of risk — an unfortunate shortcoming.
Study of the Quantification of Uncertainties in Building Life Cycle Assessment
Published in Bruno Peuportier, Fabien Leurent, Jean Roger-Estrade, Eco-Design of Buildings and Infrastructure, 2020
Marie-Lise Pannier, Patrick Schalbart, Bruno Peuportier
Knowing the best alternatives for the indicators where the choice of alternative has a significant impact on the results, an alternative can be chosen using multi-criteria decision analysis methods, for example. These methods aim to find the best compromise among several alternatives, based on the preferences of the decision-makers. It would also be useful to normalise indicators using inhabitant equivalents, which leads to the prioritisation of indicators contributing significantly to the building studied in relation to the average impact per capita. For example, if a building corresponds to the energy consumption of 100 inhabitants but only five inhabitants with regard to eutrophication, priority will be given to the least energy-consuming alternative, even if the impact of this last alternative is greater in terms of eutrophication (this should be tailored according to the local context and the actors’ priorities).
Risk Assessment in the Remediation of Hazardous Waste Sites
Published in Donald L. Wise, Debra J. Trantolo, Remediation of Hazardous Waste Contaminated Soils, 2018
Stephen T. Washburn, Jill Warnasch, Robert H. Harris
Consider a case in which both incineration and bioremediation are being evaluated as remedial alternatives for contaminated soils. A proven technology such as incineration has been shown to reduce the toxicity and volume of contaminated soil, whereas innovative technologies such as bioremediation are more experimental and pose a greater risk of failure. The costs of incineration, however, are potentially much greater than for bioremediation, and incineration remedies are often opposed by the local community. Decision tree analysis is especially helpful in this situation, where potential cost savings must be weighed against the possibility of failure and the lower likelihood of agency acceptance of innovative technologies. Using decision analysis, these risks can be explicitly and quantitatively evaluated as part of the decision-making process.
A simulation-based optimisation approach for identifying key determinants for sustainable transportation planning
Published in International Journal of Systems Science: Operations & Logistics, 2018
The quantitative approach majorly based on mathematical descriptive models uses numerical measurable indicators and is highly dependent on data. Examples of quantitative approaches are assessment indicator models (AIMs), macro-economic models, Bayesian networks, multicriteria decision analysis (MCDA), simulation and optimisation models. Tao and Hung (2003) propose three categories of AIMs namely composite index models, multilevel index models and multi-dimension matrix models. Le Pira, Inturri, Ignaccolo, and Pluchino (2015) use AHP for ranking sustainable mobility solutions. Ivanović, Grujičić, Macura, Jović, and Bojović (2013) use ANP for road transport project selection. Brey et al. (2007) use Data Envelopment Analysis for evaluation of automobiles with alternative fuels. Application of fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) in evaluating sustainable transportation systems has been reported in Awasthi, Chauhan, and Omrani (2011).
Review on multi-criteria decision analysis in sustainable manufacturing decision making
Published in International Journal of Sustainable Engineering, 2021
Anbesh Jamwal, Rajeev Agrawal, Monica Sharma, Vikas Kumar
Decision analysis in manufacturing is an important tool that helps to solve many issues characterised by multiple objectives, alternatives, and criteria (Chakraborty 2010). Generally, multi-criteria decision-making problems comprise five basic components i.e. expert preferences, the goal of the study, alternatives present for the problem, criteria available, and outcomes of the study (Pohekar and Ramachandran 2004). MCDM can be classified into three basic types which have been shown in Figure 5.