Abstract
Two approximation algorithms are presented for minimizing the makespan of independant tasks assigned on unrelated machines. The first one is based upon a partial and heuristical exploration of a search tree, which is used not only to build a solution but also to improve it thanks to a post-optimization procedure. The second implements a new large neighborhood improvement procedure to an already existing algorithm. Computational experiments show that their efficiency is equivalent to the best local search heuristics.
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Sourd, F. Scheduling Tasks on Unrelated Machines: Large Neighborhood Improvement Procedures. Journal of Heuristics 7, 519–531 (2001). https://doi.org/10.1023/A:1011960407575
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DOI: https://doi.org/10.1023/A:1011960407575