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- W1570602465 abstract "In the paper, we investigate theoretical and practical aspects of distributed computing for simulated annealing algorithms applied to the problem of scheduling l jobs on m machines. Given n = l ċ m, the total number of tasks, O(n3) processors and an upper bound Λ = Λ(l, m) of the objective function, the expected run-times of parallelized versions of our heuristics [14] are O(n ċ log n ċ log Λ) for the exponential cooling schedule and O(n2 ċ log3/2 n c˙ m1/2 ċ log Λ) for the hyperbolic one. For Markov chains of constant length, the results imply a polylogarithmic run-time O(log n ċ log(l + m)) for the exponential schedule, where we employ Λ ≤ O(l + m), see Leighton et al. [10]. We implemented a distributed version of our sequential heuristics and first computational experiments on benchmark instances are presented." @default.
- W1570602465 created "2016-06-24" @default.
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- W1570602465 date "2000-01-01" @default.
- W1570602465 modified "2023-10-01" @default.
- W1570602465 title "Distributed Simulated Annealing for Job Shop Scheduling" @default.
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- W1570602465 doi "https://doi.org/10.1007/3-540-45356-3_24" @default.
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