Acceptability of a decision maker to handle multi-objective optimization on design space

Makoto Inoue, Hibiki Matsumoto, Hideyuki Takagi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We introduce the acceptability of a decision maker to handle evolutionary multi-objective optimization (EMO) on design space, while most of EMO research tries to find many solutions on an objective space and passes them to a decision maker. Unlike this conventional EMO approaches, our approach decides maker's model with the concept of acceptability and introduces it in EMO search. Especially, this approach works well when qualitative factors, such as the decision maker's experience and knowledge on a task, are a part of evaluations. Acceptability functions for each of objectives are aggregated firstly, and the aggregated acceptability forms contours on an objective space and is mapped on a design space. The acceptability contours on a design space can narrow down the area of solutions. We could find better solutions in our experiments than the conventional approach of searching solutions on an objective space.

Original languageEnglish
Title of host publication2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728197326
DOIs
Publication statusPublished - Dec 5 2020
EventJoint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020 - Virtual, Tokyo, Japan
Duration: Dec 5 2020Dec 8 2020

Publication series

Name2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020

Conference

ConferenceJoint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020
CountryJapan
CityVirtual, Tokyo
Period12/5/2012/8/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software
  • Computational Mathematics

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