PyHasse, a Software Package for
Applicational Studies of Partial
Orderings
Rainer Bruggemann, Adalbert Kerber, Peter Koppatz, and Valentin Pratz
1 Introduction
Often a decision is to be found for a set of objects (synonym: options, alternatives)
which are highly complex. Their complexity prevents that a single criterion, i.e.,
property is sufficiently characterizing these objects in a manner that a decision can
be built on. Therefore, objects are to be characterized by a set of properties, which
indicate as to how far the objects are matching with the criterion, relevant for the
decision. In Bruggemann and Patil (2011) the term “Multi-indicator system was
introduced, just to express that the complexity of objects has its counterpart in a
whole set of indicators.
Once a set of indicators is found and a method established, as to how far these
indicators can be quantified, the next problem is, how to distill a decision. This kind
of question lead to many sophisticated Multi-criteria decision aid (MCDA) systems,
as an example PROMETHEE may be mentioned (Brans and Vincke 1985). The
field of MCDA is still increasing and a good overview can be found in Figueira
et al. (2005).
R. Bruggemann ()
Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
e-mail: brg_home@web.die
A. Kerber
Department of Mathematics, University of Bayreuth, Bayreuth, Germany
e-mail: Kerber@uni-bayreuth.de
P. Koppatz
TH Wildau Technical University of Applied Sciences Wildau, Wildau, Germany
e-mail: peter.koppatz@th-wildau.de
V. Pratz
University of Heidelberg, Gundelfingen, Germany
e-mail: pyhasse@valentinpratz.de
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
R. Bruggemann et al. (eds.), Measuring and Understanding Complex Phenomena,
https://doi.org/10.1007/978-3-030-59683-5_18
291
Applicational Studies of Partial
Orderings
Rainer Bruggemann, Adalbert Kerber, Peter Koppatz, and Valentin Pratz
1 Introduction
Often a decision is to be found for a set of objects (synonym: options, alternatives)
which are highly complex. Their complexity prevents that a single criterion, i.e.,
property is sufficiently characterizing these objects in a manner that a decision can
be built on. Therefore, objects are to be characterized by a set of properties, which
indicate as to how far the objects are matching with the criterion, relevant for the
decision. In Bruggemann and Patil (2011) the term “Multi-indicator system was
introduced, just to express that the complexity of objects has its counterpart in a
whole set of indicators.
Once a set of indicators is found and a method established, as to how far these
indicators can be quantified, the next problem is, how to distill a decision. This kind
of question lead to many sophisticated Multi-criteria decision aid (MCDA) systems,
as an example PROMETHEE may be mentioned (Brans and Vincke 1985). The
field of MCDA is still increasing and a good overview can be found in Figueira
et al. (2005).
R. Bruggemann ()
Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
e-mail: brg_home@web.die
A. Kerber
Department of Mathematics, University of Bayreuth, Bayreuth, Germany
e-mail: Kerber@uni-bayreuth.de
P. Koppatz
TH Wildau Technical University of Applied Sciences Wildau, Wildau, Germany
e-mail: peter.koppatz@th-wildau.de
V. Pratz
University of Heidelberg, Gundelfingen, Germany
e-mail: pyhasse@valentinpratz.de
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
R. Bruggemann et al. (eds.), Measuring and Understanding Complex Phenomena,
https://doi.org/10.1007/978-3-030-59683-5_18
291