An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems
Chugh, T., Sindhya, K., Hakanen, J., & Miettinen, K. (2015). An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems. In A. Gaspar-Cunha, C. H. Antunes, & C. C. Coello (Eds.), Evolutionary Multi-Criterion Optimization : 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 --April 1, 2015. Proceedings, Part I (pp. 277-291). Springer. Lecture Notes in Computer Science, 9018. https://doi.org/10.1007/978-3-319-15934-8_19
Published inLecture Notes in Computer Science
© Springer International Publishing Switzerland 2015
This paper presents a new preference based interactive evolutionary algorithm (I-SIBEA) for solving multiobjective optimization problems using weighted hypervolume. Here the decision maker iteratively provides her/his preference information in the form of identifying preferred and/or non-preferred solutions from a set of nondominated solutions. This preference information provided by the decision maker is used to assign weights of the weighted hypervolume calculation to solutions in subsequent generations. In any generation, the weighted hypervolume is calculated and solutions are selected to the next generation based on their contribution to the weighted hypervolume. The algorithm is compared with a recently developed interactive evolutionary algorithm, W-Hype on some benchmark multiobjective optimization problems. The results show significant promise in the use of the I-SIBEA algorithm. In addition, the performance of the algorithm is demonstrated using a human decision maker to show its flexibility towards changes in the preference information. The I-SIBEA algorithm is found to flexibly exploit the preference information from the decision maker and generate solutions in the regions preferable to her/him. ...
Parent publication ISBN978-3-319-15933-1
ConferenceInternational Conference on Evolutionary Multi-Criterion Optimization
Is part of publicationEvolutionary Multi-Criterion Optimization : 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 --April 1, 2015. Proceedings, Part I
ISSN Search the Publication Forum0302-9743
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