Multiple-Criteria Analysis of Life Cycle of Energy-Efficient Built Environment - Nearly Zero Energy Building Refurbishment - page 298

to specify what the definition of the best option should be. The question is
essentially one of identifying an optimal design for the option, guided by MODM
methods. Almost always, the optimization is subject to specific constraints, for
example on cost or technical specification (Multi-criteria analysis 2009 ).
The problem faced by the decision-maker is in fact a multi-objective optimi-
zation problem, characterized by the existence of multiple and competing objec-
tives, the decision space consisting in a set of feasible solutions that are not
predefined but are implicitly defined by a set of parameters and constraints that
should be taken into account. Therefore, it is not necessary to enumerate the set of
actions to be considered (Diakaki et al. 2010 ).
A number of MODM methods has been used to analyse different areas of
energy-efficient built environment such as design of building envelopes (Diakaki
et al. 2008 ), selection of heating systems (Wright et al. 2002 ), optimal thickness of
insulation (Malckzewski 1999 ), retrofit actions aimed at minimizing energy use in
a cost-effective manner (Asadi et al. 2012b ), and improving energy efficiency in
buildings (Diakaki et al. 2010 ).
MADM methods often have alternative names, too (e.g. multiple-criteria

evaluation).
There are many ways one can classify MADM methods. One way is to classify
them according to the type of the data they use. That is, we have deterministic,
stochastic or fuzzy MADM methods (for an overview of fuzzy MADM methods
(Chen and Hwang 1992 ). However, there may be situations which involve com-
binations of all the above (such as stochastic and fuzzy data) data types. Another
way of classifying MADM methods is according to the number of decision-makers
involved in the decision process. Hence, we have decision-maker MADM methods
and group decision-making MADM (Triantaphyllou et al. 1998 ).
MADM concentrates on problems with discrete decision spaces. In these
problems, the set of decision alternatives has been predetermined (Triantaphyllou
et al. 1998 ). In MADM problems with a finite number of options, each of which is
assessed in terms of a given number of criteria. For each option, with respect to
each criterion, this performance information needs to be collected. Most decisions
concern choices between a finite number of options, the details of which have
already been predetermined before they are subject to MADM. It is concerned
simply to assess the strengths and weaknesses of options as they stand and find the
best alternative (a set of good alternatives) for a decision-maker (Multi-criteria
analysis 2009 ). In a number of countries, scientists used MADM methods to solve
miscellaneous problems of energy-efficient built environment:

• local energy systems involving several energy resources (Løken 2007 );
• selection process (Malckzewski 1999 );
• selecting a heating system for a historical building (Thiel and Mroz 2001 );
• design of building envelope and refurbishment problems; selecting contractors
for public buildings (Kaklauskas et al. 2005 , 2006 );
• evaluation of conventional and renewable energy sources for household heating
(Jaber et al. 2008 ; Alanne et al. 2007 );