Performance Measurement for Interactive Multi-objective Evolutionary Algorithms

This paper suggests to use a different metric for performance of multiple-point interactive evolutionary multi-objective algorithms. We defined a preferred region based on a set of user's reference points. Based on the preferred region, we also define a User based Front (UbF) which is generated...

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Bibliographic Details
Published in:2015 Seventh International Conference on Knowledge and Systems Engineering (KSE) pp. 302 - 305
Main Authors: Long Nguyen, Hung Nguyen Xuan, Lam Thu Bui
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2015
Subjects:
Convergence
DMEA-II
Evolutionary computation
IGD
Interactive EMO
Measurement
MOEA/D
multi-point interactive
Optical fibers
Optimization
Reference points
Sociology
Statistics
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Description
Summary:This paper suggests to use a different metric for performance of multiple-point interactive evolutionary multi-objective algorithms. We defined a preferred region based on a set of user's reference points. Based on the preferred region, we also define a User based Front (UbF) which is generated from the preferred region. UbF is used in calculation of Generational Distance (GD) and Inverse Generational Distance (IGD). The usage of the metric in experiments indicated meaningful comparisons for interactive multi-objective evolutionary algorithms using multiple reference points.
DOI:10.1109/KSE.2015.51