Combining Reliability and Pareto Optimality - An Approach Using Stochastic Multi-Objective Genetic Algorithms

Abhishek Singh, Barbara Minsker, David E. Goldberg

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

Abstract

Genetic Algorithms have been successfully applied to numerous water resources problems, including problems with multiple objectives or uncertainty (noise). GAs tackle multi-objective optimization by following three basic principles - advancing the non-dominated frontier; maintaining diversity in the population (through various techniques like sharing, niching, and crowding); and using an elitist. However finding Pareto-optimal solutions becomes complicated when we add uncertainty to the problem. It was found that the solutions obtained using existing multi-objective solvers, although Pareto optimal were not the most robust or reliable solutions. In single-objective problems noise has typically been dealt with using Monte-Carlo-type sampling and some form of aggregate statistics (e.g., the average of the sample fitness). With multiple objectives the noise can interfere in determining non-domination of individuals, diversity preservation, and elitism (the three basic steps in multi-objective optimization). This paper proposes and tests several approaches to tackling some of these problems. These approaches strike a balance between finding the most optimal and the most reliable solution to the problem, thus giving decision makers and designers a practical and robust optimization tool.

Original languageEnglish (US)
Title of host publicationWorld Water and Environmental Resources Congress
EditorsP. Bizier, P. DeBarry
Pages1543-1552
Number of pages10
StatePublished - Dec 1 2003
EventWorld Water and Environmental Resources Congress 2003 - Philadelphia, PA, United States
Duration: Jun 23 2003Jun 26 2003

Publication series

NameWorld Water and Environmental Resources Congress

Other

OtherWorld Water and Environmental Resources Congress 2003
CountryUnited States
CityPhiladelphia, PA
Period6/23/036/26/03

ASJC Scopus subject areas

  • Aquatic Science
  • Water Science and Technology

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  • Cite this

    Singh, A., Minsker, B., & Goldberg, D. E. (2003). Combining Reliability and Pareto Optimality - An Approach Using Stochastic Multi-Objective Genetic Algorithms. In P. Bizier, & P. DeBarry (Eds.), World Water and Environmental Resources Congress (pp. 1543-1552). (World Water and Environmental Resources Congress).