The type-II assembly line rebalancing problem considering stochastic task learning

Abstract

Assembly lines with non-constant task time attribute are widely studied in the literature. For the SALBP-II assembly line balancing problem, we take account of stochastic task time changes, which is more practical than the deterministic times often assumed in industrial application. An algorithm – ENCORE, which leverages the traditional algorithm SALOME2, is proposed to address the assembly line balancing problem with stochastic task time attribute. Computational and statistical experiments are conducted to show the efficiency of proposed algorithms over traditional methods with regards to the improvement of total production times.

Keywords:

• assembly line balancing
• learning effects
• branch and bound
• optimisation
• production planning

Acknowledgement

I sincerely thank the four anonymous referees for their help and insights on my paper. I also would like to show my gratitude to Professor Thomas Boucher for sharing his wisdom on the earlier version of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author.