Machine scheduling problems with a general learning effect

  • Authors:
  • Xingong Zhang;Guangle Yan

  • Affiliations:
  • Business School, University of Shanghai for Science and Technology, 200093, People's Republic of China;Business School, University of Shanghai for Science and Technology, 200093, People's Republic of China

  • Venue:
  • Mathematical and Computer Modelling: An International Journal
  • Year:
  • 2010

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Abstract

Recently, learning effects in scheduling problems have received growing attention. The position-based learning model seems to be a realistic assumption for the case where the actual processing of the job is mainly machine driven. In this paper, we consider the sum-of-processing-time-based learning model. We propose a learning model which considers both the machine and human learning effects, simultaneously. We first show that the position-based learning and the sum-of-processing-time-based learning models in the literature are special cases of the proposed model. Moreover, we present the solution procedures for some single-machine and some flowshop problems.