A simulated annealing approach to mixed-model sequencing with multiple objectives on a just-in-time line

This paper presents a Simulated Annealing based heuristic that simultaneously considers both setups and the stability of parts usage rates when sequencing jobs for production in a just-in-time environment. Varying the emphasis of these two conflicting objectives is explored. Several test problems are solved via the Simulated Annealing heuristic, and their objective function values are compared to solutions obtained via a Tabu Search approach from the literature. Comparison shows that the Simulated Annealing approach provides superior results to the Tabu Search approach. It is also found that the Simulated Annealing approach provides near-optimal solutions for smaller problems.