Conference Agenda

Optimizing a building's energy supply design is an inherently multicriteria task, where not only monetary but also, for example, environmental objectives shall be taken into account. Moreover, when deciding which storages and heating and cooling units shall be purchased (here-and-now-decisions), there is also uncertainty about future developments of prices for energy, e.g. electricity and gas, that later can be accounted for by operating the units accordingly (wait-and-see-decisions), once the uncertainty revealed itself. This kind of problem is well known as an adjustable robust optimization problem. The combination of adjustable robustness and multicriteria optimization is only studied to limited extent in mathematics yet. The resulting problem can be solved using a column and constraint generation algorithm in combination with an epsilon-constraint approach.

We model the problem as a multicriteria adjustable robust problem, where we simultaneously minimize worst-case cost regret and carbon emissions. By cost regret, we mean the difference between the cost with the selected devices and the cost with the price scenario-specific optimal devices. We take into account future price uncertainties and consider the results in the light of information gap decision theory to find a trade-off between security against price fluctuations and over-conservatism. We present the model, a solution strategy and computational limits.

Multidimensional regional socio-economic analyses should take into account the complexity and spatial diversity of the European Union (EU). Using reference multi-criteria methods, this paper proposes a comprehensive framework to facilitate spatial analyses. The methodology is based on two modified multi-criteria techniques, namely TOPSIS and BIPOLAR, which include reference points for evaluation and rank-ordering objects. In TOPSIS objects are ordered directly concerning distances from the ideal and the anti-ideal points, whereas in BIPOLAR they are compared indirectly utilising two sets of reference objects: desirable (“good”) and undesirable (“bad”). Furthermore, the distinction between internal and external reference points is examined. The motivation behind this study lies in monitoring progress towards achieving Sustainable Development Goals (SDGs) in different areas while considering objectives set out in the Agenda 2030 - a complex plan of transformation for people, planet, peace, and prosperity adopted by United Nations Member States and focused on realizing 17 SDGs and 169 targets integrated into the economic, social, and environmental dimensions. To prove the usability of the proposed framework, we applied it to measure the spatial diversity of EU countries in terms of implementing SDG 11: Sustainable Cities and Communities. The analysis is conducted for the years 2015 and 2019 and is based on eight EU sustainable development indicators. The findings are showcased as rankings and depicted via maps for identifying analogous regions in the EU. The research indicates varying levels of achievement in meeting the SDG 11 objective among EU countries, with northern countries performing significantly better than southern ones.