Local search issues for the aplication of a self-adaptive hybrid genetic algorithm in groundwater remediation design

Felipe P. Espinoza, Barbara S. Minsker, David E. Goldberg

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

Abstract

Water resources management problems can be computationally intensive and improved methods are needed to allow solution of more complex applications. In this paper, we study a numerical algorithm designed to efficiently solve water resources management applications such as groundwater management problems. The algorithm is a combination of a simple genetic algorithm and a local search method and is called a self-adaptive hybrid genetic algorithm (SAHGA). The paper presents new ways to improve performance of this algorithm together with an analysis of different alternative local search algorithms. The paper also includes an analysis of the reduction in population size that is possible when using SAHGA relative to a simple genetic algorithm (SGA). The results show that the improved algorithm is more reliable and effective in solving the proposed problem, with average savings of 68% with respect to the SGA.

Original languageEnglish (US)
Title of host publicationWorld Water and Environmental Resources Congress
EditorsP. Bizier, P. DeBarry
Pages903-912
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

  • Water Science and Technology
  • Aquatic Science

Fingerprint Dive into the research topics of 'Local search issues for the aplication of a self-adaptive hybrid genetic algorithm in groundwater remediation design'. Together they form a unique fingerprint.

Cite this