A hybrid Unconscious Search algorithm for mixed-model assembly line balancing problem with SDST, parallel workstation and learning effect

Document Type: Original Manuscript

Authors

1 Department of Industrial ans Systems Engineering, Tarbiat Modares University, Tehran, Iran

2 Department of Industrial Engineering, Islamic Azad University Karaj Branch,Alborz,Iran

3 Department of Industrial Engineering, Islamic Azad University Karaj Branch, Alborz, Iran

10.22094/joie.2020.579974.1605

Abstract

Due to the variety of products, simultaneous production of different models has an important role in production systems. Moreover, considering the realistic constraints in designing production lines attracted a lot of attentions in recent researches. Since the assembly line balancing problem is NP-hard, efficient methods are needed to solve this kind of problems. In this study, a new hybrid method based on unconscious search algorithm (USGA) is proposed to solve mixed-model assembly line balancing problem considering some realistic conditions such as parallel workstation, zoning constraints, sequence dependent setup times and learning effect. This method is a modified version of the unconscious search algorithm which applies the operators of genetic algorithm as the local search step. Performance of the proposed algorithm is tested on a set of test problems and compared with GA and ACOGA. The experimental results indicate that USGA outperforms GA and ACOGA.

Graphical Abstract

A hybrid Unconscious Search algorithm for mixed-model assembly line balancing problem with SDST, parallel workstation and learning effect

Highlights

  • To improve the search ability of the proposed algorithm, the Unconscious Search algorithm is hybridized with operators of genetic algorithm.
  • Several real-world constraints such as parallel workstation, zoning constraints, sequence dependent setup times and learning effect are considered in the mixed model assembly line balancing problem.
  • The steps of the proposed algorithm are well explained using pseudo codes, figures and flowcharts.

Keywords


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