Faster min–max resource sharing in theory and practice

Faster min–max resource sharing in theory and practice
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理论和实践中更快的最小最大资源共享

DOI:
10.1007/s12532-011-0023-y
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发表时间:
2011
影响因子:
6.3
通讯作者:
J. Vygen
J. Vygen
中科院分区:
数学2区
文献类型:
--
作者:
D. Müller;K. Radke;J. Vygen

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We consider the (block-angular) min–max resource sharing problem, which is defined as follows. Given finite setsof resources andof customers, a convex set, called block, and a convex functionfor every, the task is to findapproximately attaining $${\lambda^*:=\inf\{\max_{r\in\mathcal{R}}\sum_{c\in\mathcal{C}}(g_c(b_c))_r \mid b_c\in\mathcal{B}_c\ (c\in\mathcal{C})\}}$$. As usual we assume thatgccan be computed efficiently and we have a constantσ≥ 1 and oracle functions, called block solvers, which forandreturn an elementwith. We describe a simple algorithm which solves this problem with an approximation guaranteeσ(1 +ω) for anyω> 0, and whose running time isfor any fixedσ≥ 1, whereθis the time for an oracle call. This generalizes and improves various previous results. We also prove other bounds and describe several speed-up techniques. In particular, we show how to parallelize the algorithm efficiently. In addition we review another algorithm, variants of which were studied before. We show that this algorithm is almost as fast in theory, but it was not competitive in our experiments. Our work was motivated mainly by global routing in chip design. Here the blocks are mixed-integer sets (whose elements are associated with Steiner trees), and we combine our algorithm with randomized rounding. We present experimental results on instances resulting from recent industrial chips, with millions of customers and resources. Our algorithm solves these instances nearly optimally in less than two hours.
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