A Mixture-of-Experts Prediction Framework for Evolutionary Dynamic Multiobjective Optimization

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

9 Scopus Citations
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Detail(s)

Original languageEnglish
Article number8698315
Pages (from-to)5099-5112
Journal / PublicationIEEE Transactions on Cybernetics
Volume50
Issue number12
Online published24 Apr 2019
Publication statusPublished - Dec 2020

Abstract

Dynamic multiobjective optimization requires the robust tracking of varying Pareto-optimal solutions (POS) in a changing environment. When a change is detected in the environment, prediction mechanisms estimate the POS by utilizing information from previous populations to accelerate search toward the true POS. To achieve a robust prediction of POS, a mixture-of-experts-based ensemble framework is proposed. Unlike existing approaches, the framework utilizes multiple prediction mechanisms to improve the overall prediction. A gating network is applied to manage switching among the various predictors based on performance of the predictors at different time intervals of the optimization process. The efficacy of the proposed framework is validated through experimental studies based on 13 dynamic multiobjective benchmark optimization problems. The simulation results show that the proposed framework improves the dynamic optimization performance significantly, particularly for: 1) problems with distinct dynamic POS in decision space over time and 2) problems with highly nonlinear decision variable linkages.

Research Area(s)

  • Dynamic multiobjective optimization, evolutionary algorithms (EAs), mixture-of-experts (MoE)

Citation Format(s)

A Mixture-of-Experts Prediction Framework for Evolutionary Dynamic Multiobjective Optimization. / Rambabu, Rethnaraj; Vadakkepat, Prahlad; Tan, Kay Chen; Jiang, Min.

In: IEEE Transactions on Cybernetics, Vol. 50, No. 12, 8698315, 12.2020, p. 5099-5112.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review