A novel bi-level hierarchy towards available-to-promise in mixed-model assembly line sequencing problems

Abstract

This article addresses advanced available-to-promise (AATP) in mixed-model assembly line sequencing problems. In the developed framework, customers are prioritized with respect to 11 defined criteria using the technique for order of preference by similarity to ideal solution (TOPSIS) method, and order quantities are calculated using a nonlinear mathematical program. Next, a mixed binary nonlinear mathematical program is developed to determine the optimum sequence of the optimized order quantities to minimize the total lateness. Since the proposed models are intractable, a hybrid genetic algorithm–simulated annealing method is also developed. Finally, an industrial case study is reported, the results of which validate the developed AATP framework.

Keywords:

• advanced available-to-promise
• genetic algorithm
• mixed-model assembly line
• simulated annealing
• penalty cost

Funding

The authors would like to acknowledge the financial support of the University of Tehran for this research [grant no. 8109002/1/10].