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Moreover, benders decomposition is integrated with scenario reduction technique to solve the large-scale instances.
Therefore, we propose a fast heuristic to solve large-scale instances within acceptable time durations.
It is further observed that GPA outperforms other approaches even for large-scale instances.
The experimental result obtained confirms the applicability on large-scale instances.
We implemented a parallel version of this heuristic and report computational experiments on large-scale instances.
Different diversification strategies are tested and compared on large-scale instances with up to 500 vertices.
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Detroit, more than a mere metaphor, is a striking and large-scale instance of something that has become pervasively wrong in America.
For solving large scale instances we implemented an Ant Colony Optimization procedure.
Secondly, four heuristics are proposed to investigate the performance for moderate and large scale instances.
A decomposition based algorithm was developed and combined with enhancement strategies to solve optimally large scale instances.
The efficiency is evaluated using the widely known 40 Laurence's instances which encompass medium and large scale instances.
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