2011
DOI: 10.1016/j.cie.2011.02.005
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Computational complexity and solution algorithms for flowshop scheduling problems with the learning effect

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Cited by 55 publications
(18 citation statements)
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“…It follows from the observations that algorithms constructed on the basis of the classical models usually provide unsatisfactory (unstable) solutions for real-life flowshop problems, since these models do not take into consideration additional factors that are significant in practice, e.g. sequence-dependent setup times [16,20] or variable processing times [2,4,5,23,27,31]. To this group belong the described real-life problems, where a deterioration of machines (understood as chemical cleaning baths, lathe machines, human workers etc.)…”
mentioning
confidence: 99%
“…It follows from the observations that algorithms constructed on the basis of the classical models usually provide unsatisfactory (unstable) solutions for real-life flowshop problems, since these models do not take into consideration additional factors that are significant in practice, e.g. sequence-dependent setup times [16,20] or variable processing times [2,4,5,23,27,31]. To this group belong the described real-life problems, where a deterioration of machines (understood as chemical cleaning baths, lathe machines, human workers etc.)…”
mentioning
confidence: 99%
“…They provide a branch-and-bound algorithm that could solve instances with up to 16 jobs. Rudek (2011) studies the two-machine flowshop problem to minimize the makespan. He shows that an optimal solution is not necessarily a permutation schedule when the learning effect is taken into consideration.…”
Section: Introductionmentioning
confidence: 99%
“…They showed some single-machine problems remain polynomially solvable. Rudek [20] analyzed the makespan problem on two-machine flowshop with learning effects. First, he showed that an optimal solution of this problem does not have to be the 'permutation' schedule if the learning effect is taken into consideration.…”
Section: Introductionmentioning
confidence: 99%