Comparing two weighted approaches for sequencing mixed-model assembly lines with multiple objectives

This paper compares two weighted approaches in sequencing mixed-model assembly lines for a joint objective of multiple objectives. Minimizing the weighted sum of percentage differences from the best solution values of the respective objectives is considered as the joint objective. A solution that achieves this joint objective is considered a “jointly balanced” solution. The scaling method attempts to normalize all the terms in the various objectives; and the goal method applies weights through a two-pass procedure. In performing computational experimentation of the scaling and goal methods, the heuristic method of minimizing the weighted two-stage variation is employed. Computational results showed that the goal method generally obtained more jointly balanced solutions than the scaling method. Furthermore, results from the scaling and goal methods can likely be improved by an enhancement procedure. The goal method was also compared to an existing parametric procedure for a combination of four objectives, and the results showed that the goal method performed relatively well. Potential interaction among the various objectives is also discussed.