A survey on benders decomposition applied to fixed-charge network design problems
Computers and Operations Research
Balancing of mixed-model two-sided assembly lines
Computers and Industrial Engineering
Computers and Operations Research
A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II
Computers and Industrial Engineering
Computers and Industrial Engineering
A solution procedure for type E simple assembly line balancing problem
Computers and Industrial Engineering
Enhanced mixed integer programming model for a transfer line design problem
Computers and Industrial Engineering
Stability measure for a generalized assembly line balancing problem
Discrete Applied Mathematics
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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.