Assembly line balancing under uncertainty: Robust optimization models and exact solution method

• A robust optimization approach for assembly line balancing is presented.
• Mathematical models for interval uncertainty of operation times are suggested.
• Decomposition based solution algorithms are developed.
• Techniques proposed generate designs that are more protected against disruptions.
• Approach proposed can be extended to large class of line balancing problems.

This research deals with line balancing under uncertainty and presents two robust optimization models. Interval uncertainty for operation times was assumed. The methods proposed generate line designs that are protected against this type of disruptions. A decomposition based algorithm was developed and combined with enhancement strategies to solve optimally large scale instances. The efficiency of this algorithm was tested and the experimental results were presented. The theoretical contribution of this paper lies in the novel models proposed and the decomposition based exact algorithm developed. Moreover, it is of practical interest since the production rate of the assembly lines designed with our algorithm will be more reliable as uncertainty is incorporated. Furthermore, this is a pioneering work on robust assembly line balancing and should serve as the basis for a decision support system on this subject.