Abstract
In this paper, metaheuristic approaches for the weighted late work minimization in the two-machine flow shop problem with a common due date (F2 | d j =d | Y w ) are presented. The late work performance measure estimates the quality of a solution with regard to the duration of the late parts of jobs not taking into account the quantity of the delay for the fully late activities. Since, the problem mentioned is known to be NP-hard, three trajectory based methods, namely simulated annealing, tabu search and variable neighborhood search were designed and compared to an exact approach and a list scheduling algorithm.
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Blazewicz, J., Pesch, E., Sterna, M., Werner, F. (2005). Metaheuristics for Late Work Minimization in Two-Machine Flow Shop with Common Due Date. In: Furbach, U. (eds) KI 2005: Advances in Artificial Intelligence. KI 2005. Lecture Notes in Computer Science(), vol 3698. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11551263_19
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DOI: https://doi.org/10.1007/11551263_19
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