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Efficient Resource Constrained Scheduling Using Parallel Two-Phase Branch-and-Bound Heuristics
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DOI：10.1109/TPDS.2016.2621768.png)
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摘要
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Branch-and-bound (B&B) approaches are widely investigated in resource constrained scheduling (RCS). However, due to the lack of approaches that can generate a tight schedule at the beginning of the search, B&B approaches usually start with a large initial search space, which makes the following search of an optimal schedule time-consuming. To address this problem, this paper proposes a parallel two-phase B&B approach that can drastically reduce the overall RCS time. This paper makes three major contributions: i) it proposes three partial-search heuristics that can quickly find a tight schedule to compact the initial search space; ii) it presents a two-phase search framework that supports the efficient parallel search of an optimal schedule; iii) it investigates various bound sharing and speculation techniques among collaborative tasks to further improve the parallel search performance at different search phases. The experimental results based on well-established benchmarks demonstrate the efficacy of our proposed approach.
Keyword:
Resource constrained scheduling
branch-and-bound
parallel two-phase pruning
high-level synthesis
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