Title

Handling Uncertainty In Evolutionary Multiobjective Optimization: Spga

Abstract

This paper presents an extension of the previously developed approach to solve multiobjective optimization problems in deterministic environments by incorporating a stochastic Pareto-based solution ranking procedure. The proposed approach, called stochastic Pareto genetic algorithm (SPGA), employs some statistical analysis on the solution dominance in stochastic problem environments to better discriminate among the competing solutions. Preliminary computational results on three published test problems for different levels of noise with SPGA and NSGA-II are discussed. ©2007 IEEE.

Publication Date

12-1-2007

Publication Title

2007 IEEE Congress on Evolutionary Computation, CEC 2007

Number of Pages

4130-4137

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/CEC.2007.4425010

Socpus ID

79955223416 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/79955223416

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