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GA based algorithm for staff scheduling considering learning-forgetting effect

  • Ji Hong Yan*
  • , Zi Mo Wang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Learning-forgetting effect reflects productivity changes related to the increment of experience cumulated by previous production volume, which is a critical issue for production efficiency analysis. This paper proposes a GA based staff scheduling methodology for solving personnel efficiency problem caused by learning-forgetting effect, aiming at obtaining scheduling solution in both parallel and serial systems. Individual capability is modeled considering his/her initial and maximum capabilities, as well as learning/forgetting rates on corresponding tasks. Two experiments are designed in scenarios for parallel and serial production lines and strategies of staff scheduling are generated considering learning-forgetting phenomenon. Simulation results illustrate the effectiveness of the proposed methodology.

Original languageEnglish
Title of host publication2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management, IE and EM 2011
Pages122-126
Number of pages5
EditionPART 1
DOIs
StatePublished - 2011
Event2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management, IE and EM 2011 - Changchun, China
Duration: 3 Sep 20115 Sep 2011

Publication series

Name2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management, IE and EM 2011
NumberPART 1

Conference

Conference2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management, IE and EM 2011
Country/TerritoryChina
CityChangchun
Period3/09/115/09/11

Keywords

  • Genetic algorithm
  • Learning-forgetting Effect
  • Staff scheduling

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