Quality assessment of multiobjective optimisation algorithms in component deployment

Authors:
Aldeida Aleti
Affiliations:
Swinburne University of Technology, Melbourne, Australia
Venue:
Proceedings of the doctoral symposium for ESEC/FSE on Doctoral symposium
Year:
2009

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Abstract

Measuring the quality of the approximate sets in a quantitative way is important to asses the performance of multiobjective optimisation algorithms and decide which algorithm performs best in a problem domain. In the case of component deployment optimisation of automotive systems, despite the wide range of optimisation methods already published, it is still unknown which algorithm is the optimal choice. Several studies can be found in the literature that address the problem of comparing approximate sets in a quantitative manner, reflecting a specific feature of the optimisation method, i.e. either convergence or diversity. However, both convergence and diversity are important quality aspects and both should be considered to define dominance relations. The aim of this study is a new quality assessment method for approximate sets, which will indicate dominance relations based on both convergence and diversity.