Abstract
The paper considers multiprocessor task scheduling in multistage hybrid flowshops. To solve the above problem a population based approach is suggested. The population learning algorithm based on several local search procedures has been proposed and implemented. The algorithm has been evaluated by means of a computational experiment in which 160 benchmark instances have been solved and compared with the available upper bounds. It has been possible to improve 45% of previously known upper bounds.
Cite
CITATION STYLE
Jȩdrzejowicz, J., & Jȩdrzejowicz, P. (2003). Population-based approach to multiprocessor task scheduling in multistage hybrid flowshops. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2773 PART 1, pp. 279–286). https://doi.org/10.1007/978-3-540-45224-9_40
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