Comprehensive Methods for Dealing with Uncertainty in Assessing Sustainability Part 1: The MIVES – Monte Carlo Method

Integrated Value Method for Sustainability Evaluation (MIVES) is a deterministic method based on requirement trees, value functions, and the Analytic Hierarchy Process. It allows integrating environmental, social, and economic sustainability indicators in a global index. The value functions make it possible to consider non-linearity in the assessment. MIVES takes into account the relative weight of the various model indicators. Deterministic models can cause significant problems in terms of adequately managing project sustainability. A method not only has to estimate the sustainability index at the end of the project. It also has to evaluate the degree of uncertainty that may make it difficult to achieve the sustainability objective. Uncertainty can affect indicators, weights, and value function shapes. This chapter presents a method for sustainability assessment, taking into account uncertainty. It is based on MIVES and the Monte Carlo simulation technique. An example of potential application is proposed, related to power plants. Comprehensive Methods for Dealing with Uncertainty in Assessing Sustainability Part 1: The MIVES – Monte Carlo Method

[1]  José T. San-José,et al.  Health & Safety criteria for determining the sustainable value of construction projects , 2014 .

[2]  N. Metropolis,et al.  The Monte Carlo method. , 1949 .

[3]  Jim Freeman,et al.  The Influence of Experience and Information Search Styles on Project Risk Identification Performance , 2007, IEEE Transactions on Engineering Management.

[4]  Byeong Seok Ahn,et al.  Determining Multiple Attribute Weights Consistent with Pairwise Preference Orders , 2005, ICCSA.

[5]  Jesús Cuadrado Rojo,et al.  Industrial building design stage based on a system approach to their environmental sustainability , 2010 .

[6]  Salah E. Elmaghraby,et al.  On the fallacy of averages in project risk management , 2005, Eur. J. Oper. Res..

[7]  H. Noll,et al.  Towards a European System of Social Indicators: Theoretical Framework and System Architecture , 2002 .

[8]  Jonathan Burton,et al.  Is small beautiful? A multicriteria assessment of small-scale energy technology applications in local governments , 2007 .

[9]  Quirico Semeraro,et al.  A new method to cope with decision makers' uncertainty in the equipment selection process , 2004 .

[10]  Terry Williams,et al.  The two-dimensionality of project risk , 1996 .

[11]  Paul Upham,et al.  Public and stakeholder perceptions of 2030 bioenergy scenarios for the Yorkshire and Humber region , 2007 .

[12]  R. C. Van den Honert,et al.  Stochastic group preference modelling in the multiplicative AHP: A model of group consensus , 1998, Eur. J. Oper. Res..

[13]  A. Stam,et al.  Stochastic Judgments in the AHP: The Measurement of Rank Reversal Probabilities , 1997 .

[14]  T. Saaty.  Fundamentals of Decision Making and Priority Theory With the Analytic Hierarchy Process , 2000 .

[15]  E. Forman.  Random indices for incomplete pairwise comparison matrices , 1990 .

[16]  Richard Kielbasa,et al.  Latin Hypercube Sampling Monte Carlo Estimation of Average Quality Index for Integrated Circuits , 1997 .

[17]  Luis A. Bojórquez-Tapia,et al.  Building Consensus in Environmental Impact Assessment Through Multicriteria Modeling and Sensitivity Analysis , 2005, Environmental management.

[18]  C. H. Han,et al.  Tools for establishing dominance with linear partial information and attribute hierarchy , 2004, Int. J. Syst. Sci..

[19]  Cengiz Kahraman,et al.  Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul , 2010 .

[20]  Alfredo del Caño,et al.  Uncertainty analysis in the sustainable design of concrete structures: A probabilistic method , 2012 .

[21]  J. Antony,et al.  Modified analytic hierarchy process to incorporate uncertainty and managerial aspects , 2004 .

[23]  H Scott Matthews,et al.  Life Cycle Impact Assessment: A Challenge for Risk Analysts , 2002, Risk analysis : an official publication of the Society for Risk Analysis.

[24]  A. Josa,et al.  A Value Function for Assessing Sustainability: Application to Industrial Buildings , 2010 .

[25]  Eduardo Rojí,et al.  Sustainability index for industrial buildings , 2012 .

[26]  Terry Williams,et al.  Practical Use of Distributions in Network Analysis , 1992 .

[27]  Alfredo del Caño,et al.  Integrated Methodology for Project Risk Management , 2002 .

[28]  K. Davidson,et al.  A corporate social responsibility indicator system for construction enterprises , 2012 .

[29]  Agis M. Papadopoulos,et al.  Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems , 2008 .

[30]  Danae Diakoulaki,et al.  Multi-criteria decision analysis and cost–benefit analysis of alternative scenarios for the power generation sector in Greece , 2007 .

[31]  Diana Gallego Carrera,et al.  Sustainability assessment of energy technologies via social indicators: Results of a survey among European energy experts , 2010 .

[32]  Robert J. Chapman,et al.  The controlling influences on effective risk identification and assessment for construction design management , 2001 .

[33]  Eugene D. Hahn.  Decision Making with Uncertain Judgments: A Stochastic Formulation of the Analytic Hierarchy Process , 2003, Decis. Sci..

[34]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[35]  Alfredo del Caño,et al.  Sustainability Assessment of Concrete Structures within the Spanish Structural Concrete Code , 2012 .

[36]  José-Tomás San-José Lombera,et al.  A system approach to the environmental analysis of industrial buildings , 2010 .

[37]  Cathal M. Brugha,et al.  Structure of multi-criteria decision-making , 2004, J. Oper. Res. Soc..

[38]  Luis G. Vargas,et al.  Uncertainty and rank order in the analytic hierarchy process , 1987 .

[39]  Inna Krykova,et al.  Evaluating of path-dependent securities with low discrepancy methods , 2003 .

[40]  Reinhard Madlener,et al.  New ways for the integrated appraisal of national energy scenarios: The case of renewable energy use in Austria , 2007 .

[41]  Reinhard Madlener,et al.  Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis , 2009, Eur. J. Oper. Res..

[42]  Robert J. Chapman,et al.  The effectiveness of working group risk identification and assessment techniques , 1998 .

[43]  E. Rosenbloom.  A probabilistic interpretation of the final rankings in AHP , 1997 .

[44]  Jyh-Rong Chou,et al.  A Gestalt-like perceptual measure for home page design using a fuzzy entropy approach , 2006, Int. J. Hum. Comput. Stud..

[45]  Oriol Pons,et al.  Integrated value model for sustainable assessment applied to technologies used to build schools in Catalonia, Spain , 2012 .