Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Simulated annealing: theory and applications
Simulated annealing: theory and applications
A systematic procedure for setting parameters in simulated annealing algorithms
Computers and Operations Research
An evolutionary approach to multi-objective scheduling of mixed model assembly lines
Computers and Industrial Engineering
A Lagrangean relaxation approach for the mixed-model flow line sequencing problem
Computers and Operations Research
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The effectiveness of the solution method based on simulated annealing (SA) mainly depends on how to determine the SA-related parameters. A scheme as well as parameter values for defining an annealing schedule should be appropriately determined, since various schemes and their corresponding parameter values have a significant impact on the performance of SA algorithms. In this paper, based on robust design we propose a new annealing parameter design method for the mixed-model sequencing problem which is known to be NP-hard. To show the effectiveness of the proposed method, extensive computation experiments are conducted. It was found that the robust designed method outperforms the SA algorithm by McMullen and Frazier [McMullen, P.R., & Frazier, G.V. (2000). A simulated annealing approach to mixed-model sequencing with multiple objectives on a just-in-time line. IIE Transactions, 32, 679-686].