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Titlebook: Life Cycle Inventory Analysis; Methods and Data Andreas Ciroth,Rickard Arvidsson Book 2021 The Editor(s) (if applicable) and The Author(s),

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發(fā)表于 2025-3-26 21:14:53 | 只看該作者
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發(fā)表于 2025-3-27 02:27:00 | 只看該作者
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發(fā)表于 2025-3-27 05:48:51 | 只看該作者
Xiaojin Zhang,Hongtao Wang,Karin Treyer requiring as yet unavailable resources. Processors are frequently the resource involved and the purpose of backfilling is to increase system utilization and reduce average wait time. Generally, a scheduler backfills when the user-specified run times indicate that executing the lower priority jobs w
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發(fā)表于 2025-3-27 11:04:27 | 只看該作者
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發(fā)表于 2025-3-27 17:10:13 | 只看該作者
Andreas Cirothing problem. The problem is exacerbated by uncertainties in demand and availability of resources. In this paper, we present a stochastic optimization based framework for robust decision making in the selection of distributed resources over a planning horizon under demand uncertainty. We present a no
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發(fā)表于 2025-3-28 04:26:32 | 只看該作者
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發(fā)表于 2025-3-28 09:56:52 | 只看該作者
Jutta Hildenbrand,Rickard Arvidssonrce allocation is known to provide the flexibility needed to obtain better response times under such conditions. We present a scheduling approach (SCOJO-P) which decides resource allocation, i.e. the number of processors, at job start time and then keeps the allocation fixed throughout the execution
40#
發(fā)表于 2025-3-28 10:41:43 | 只看該作者
arallel jobs can be run on different processor partition sizes, but there is often a trade-off between wait-time and run-time — asking for many processors reduces run-time but may require a protracted wait. With moldable scheduling, the choice of job partition size is determined by the scheduler, us
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