Multi-criteria decision making under uncertainty in building performance assessment

Abstract

Multi-criteria decision making under uncertainty in building performance assessment. Building and Environment, 69, Additional Information:• This is the author's version of a work that was accepted for publication in Building and Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published at: AbstractBuilding performance assessment is complex, as it has to respond to multiple criteria.Objectives originating from the demands that are put on energy consumption, acoustical performance, thermal occupant comfort, indoor air quality and many other issues must all be reconciled. An assessment requires the use of predictive models that involve numerous design and physical parameters as their inputs. Since these input parameters, as well as the models that operate on them, are not precisely known, it is imprudent to assume deterministic values for them. A more realistic approach is to introduce ranges of uncertainty in the parameters themselves, or in their derivation, from underlying approximations. In so doing, it is recognized that the outcome of a performance assessment is influenced by many sources of uncertainty.As a consequence of this approach the design process is informed by assessment outcomes that produce probability distributions of a target measure instead of its deterministic value. In practice this may lead to a "well informed" analysis but not necessarily to a straightforward, cost effective and efficient design process. This paper discusses how design decision making can be based on uncertainty assessments. A case study is described focusing on a discrete decision that involves a choice between two HVAC system designs. Analytical hierarchy process (AHP) including uncertainty information is used to arrive at a rational decision. In this approach, key performance indicators such as energy efficiency, thermal comfort and others are ranked according to their importance and preferences. This process enables a clear group consensus based choice of one of the two options. The research presents a viable means of collaboratively ranking complex design options based on stakeholder's preferences and considering the uncertainty involved in the designs. In so doing it provides important feedback to the design team.

A Decision Rule for Uncertain Multi-Criteria Pure Decision Making and Independent Criteria

“…Many classical and extended decision rules designed for pure or mixed MDMU (multi-criteria decision-making under uncertainty) have been already developed, e.g. [Aghdaie et al, 2013;Ben Amor et al, 2007;Dominiak, 2006;Durbach, 2014;Eiselt, Marianov, 2014;GasparsWieloch, 2014d;2015c;2015d;2017;Ginevičius, Zubrecovas, 2009;Goodwin, Wright, 2001;Hopfe et al, 2013;Janjic et al, 2013;Korhonen, 2001;Lee, 2012;Liu et al, 2011;Lo, Michnik, 2010;Michnik, 2013;Mikhaidov, Tsvetinov, 2004;Montibeller et al, 2006;Ram et al, 2010;Ramik et al, 2008;Ravindran, 2008;Silva, 2016;Stewart, 2005;Suo et al, 2012;Troutt, Pettypool, 1989;Tsaur et al, 2002;Urli, Nadeau, 2004;Wojewnik, Szapiro, 2010;Xu, 2000;Yu, 2002]. Some of them can be applied when the DM intends to perform the selected alternative only once (one-shot decisions).…”

The use of multi-criteria optimization to choose solutions for energy-efficient buildings

“…However, every time the air quality in the building must be taken under consideration -this is possible, in case of the low energy buildings, only through the airflow control and heat recovery. The use of multi-criteria optimization to choose solutions for energy-efficient buildings rate analyses the different permissible solutions can be found [14][15][16][17][38][39][40][41][42][43]. The multi-criteria analysis, proposed in this paper, allows for a classification of the alternative, technical solutions regarding HVAC systems and building itself designing taking under consideration: the economics, energy, environmental parameters in terms of complex energy-related optimum, keeping in the same time all limiting conditions.…”

Developing a Fuzzy Analytic Hierarchy Process for Choosing the Energetically Optimal Solution at the Early Design Phase of a Building

“…Lifetime and reliability refer to the longevity and maintainability of all structures and equipment considered in the other main criteria. Another important criterion is investment cost, but at this stage of our work we have not yet integrated this criterion into our research, similarly to other international researchers [8]. The pay-off of the investments strongly depends on energy prices and thus needs to be inspected separately, which is not the subject of this article.…”