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.
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Jędrzejowicz, J., Jędrzejowicz, P. (2003). Population-Based Approach to Multiprocessor Task Scheduling in Multistage Hybrid Flowshops. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_40
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DOI: https://doi.org/10.1007/978-3-540-45224-9_40
Publisher Name: Springer, Berlin, Heidelberg
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