Finding robust pareto-optimal solutions using geometric angle-based pruning algorithm
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Publication Details
Author list: Sudeng S., Wattanapongsakorn N.
Publisher: Springer Verlag
Publication year: 2014
Volume number: 542
Start page: 277
End page: 295
Number of pages: 19
ISBN: 9783319047010
ISSN: 1860-949X
eISSN: 1860-949X
Languages: English-Great Britain (EN-GB)
Abstract
Evolutionary multi-objective optimization algorithms have been developed to find a representative set of Pareto-optimal solutions in the past decades. However, researchers have pointed out that finding a representative set of Pareto-optimal solutions is not sufficient; the task of choosing a single preferred Pareto-optimal solution is also another important task which has received a widespread attention so far. In this paper, we propose an algorithm to help the decision maker (DM) choose the final preferred solution based on his/her preferred objectives. Our algorithm is called an adaptive angle based pruning algorithm with independent bias intensity tuning parameter (ADA-τ). The method begins by calculating the angle between a pair of solutions by using a simple arctangent function. The bias intensity parameter of each objective is introduced independently in order to approximate the portions of desirable solutions based on the DM's preferred objectives. We consider several benchmark problems including two and three-objective problems. The experimental results have shown that our pruning algorithm provides a robust sub-set of Pareto-optimal solutions for the benchmark problems. © 2014 Springer International Publishing Switzerland.
Keywords
Multi-Objective Optimization, Pareto-optimal solutions, Pruning algorithm
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