A single-machine bi-criterion learning scheduling problem with release times

  • Authors:
  • Wen-Chiung Lee;Chin-Chia Wu;Ming-Fang Liu

  • Affiliations:
  • Department of Statistics, Feng Chia University, Taichung, Taiwan, ROC;Department of Statistics, Feng Chia University, Taichung, Taiwan, ROC;Department of Statistics, Feng Chia University, Taichung, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

The learning effect in scheduling has received considerable attention recently. However, most researchers consider a single criterion with the assumption that jobs are all ready to be processed. The research of bi-criterion problems with learning effect is relatively limited. This paper studies a single-machine learning effect scheduling problem with release times where the objective is to minimize the sum of makespan and total completion time. First, we develop a branch-and-bound algorithm incorporating with several dominance properties and a lower bound to derive the optimal solution. Secondly, we propose a genetic algorithm to obtain near-optimal solutions. Finally, a computational experiment is conducted to evaluate the performance of the branch-and-bound and the genetic algorithms.