Evolutionary algorithms under noise and uncertainty: A location-allocation case study

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1 Citation (Scopus)
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Abstract

Evolutionary approaches are metaheuristics that can deal with the effect of noise and uncertainty in data using different strategies. In this paper is depicted the method used to cope with these elements in a dynamical location-allocation problem. The use of Monte Carlo sampling and statistical historical data that can be applied to a single and multi-objective problems and within an online and offline scenario is tested and evaluated.

Original languageEnglish
Title of host publication2016 IEEE Symposium Series on Computational Intelligence (SSCI)
PublisherIEEE
ISBN (Electronic)9781509042401
DOIs
Publication statusPublished - 13 Feb 2017
Event2016 IEEE Symposium Series on Computational Intelligence - Athens, Greece
Duration: 6 Dec 20169 Dec 2016

Conference

Conference2016 IEEE Symposium Series on Computational Intelligence
Abbreviated titleSSCI 2016
CountryGreece
CityAthens
Period6/12/169/12/16

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Control and Optimization
  • Artificial Intelligence

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