Towards Automatic Testing of Reference Point Based Interactive Methods
Ojalehto, V., Podkopaev, D., & Miettinen, K. (2016). Towards Automatic Testing of Reference Point Based Interactive Methods. In J. Handl, E. Hart, P. R. Lewis, M. López-Ibáñez, G. Ochoa, & B. Paechter (Eds.), Parallel Problem Solving from Nature – PPSN XIV : 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings (pp. 483-492). Lecture Notes in Computer Science, 9921. Springer International Publishing. doi:10.1007/978-3-319-45823-6_45
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Lecture Notes in Computer Science;9921Date
2016Discipline
TietotekniikkaCopyright
© Springer International Publishing AG. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.
In order to understand strengths and weaknesses of optimization
algorithms, it is important to have access to different types of
test problems, well defined performance indicators and analysis tools.
Such tools are widely available for testing evolutionary multiobjective
optimization algorithms.
To our knowledge, there do not exist tools for analyzing the performance
of interactive multiobjective optimization methods based on the
reference point approach to communicating preference information. The
main barrier to such tools is the involvement of human decision makers
into interactive solution processes, which makes the performance of interactive
methods dependent on the performance of humans using them.
In this research, we aim towards a testing framework where the human
decision maker is replaced with an artificial one and which allows to
repetitively test interactive methods in a controlled environment.