Title :
Preference-based multi-objective software modelling
Author :
Mkaouer, Mohamed W. ; Kessentini, Marouane ; Bechikh, Slim ; Tauritz, Daniel R.
Author_Institution :
Dept. of Comput. Sci., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
Abstract :
In this paper, we propose the use of preference-based evolutionary multi-objective optimization techniques (P-EMO) to address various software modelling challenges. P-EMO allows the incorporation of decision maker (i.e., designer) preferences (e.g., quality, correctness, etc.) in multi-objective optimization techniques by restricting the Pareto front to a region of interest easing the decision making task. We discuss the different challenges and potential benefits of P-EMO in software modelling. We report experiments on the use of P-EMO on a well-known modeling problem where very promising results are obtained.
Keywords :
decision making; evolutionary computation; software engineering; P-EMO; Pareto front; decision making task; preference-based evolutionary multiobjective software modelling; Adaptation models; Computational modeling; Measurement; Optimization; Software; Software algorithms; Software engineering; Search-based software engineering; evolutionary computation; modelling; multi-objective optimization; user-preferences;
Conference_Titel :
Combining Modelling and Search-Based Software Engineering (CMSBSE), 2013 1st International Workshop on
Conference_Location :
San Francisco, CA
DOI :
10.1109/CMSBSE.2013.6605712