低风险环境下的最优约束资源分配策略
Optimal Constrained Resource Allocation Strategies under Low Risk Circumstances
摘要：
在本文中，我们考虑多约束资源分配问题，其中的约束可以指定通过制定活动依赖限制或使用博弈论模型。所有的问题都集中在一般资源上，只有少数例外，特别考虑到财政资源。该问题考虑低风险的情况下，算法所使用的不确定变量的值是变量的期望值。对于每一个考虑的问题，我们提出了新的算法解决方案，计算最佳的资源分配策略。从时间复杂度的角度来看，所提出的解决方案是最优或接近最优的。所考虑的问题在广泛的领域中具有应用，如工业（例如，在采矿和冶金工业中）或金融部门中的工作流调度、运动规划、设施位置和数据传输或网格、云或其他分布式系统中的作业调度和资源管理。
英文摘要：
In this paper we consider multiple constrained resource allocation problems, where the constraints can be specified by formulating activity dependency restrictions or by using game-theoretic models. All the problems are focused on generic resources, with a few exceptions which consider financial resources in particular. The problems consider low-risk circumstances and the values of the uncertain variables which are used by the algorithms are the expected values of the variables. For each of the considered problems we propose novel algorithmic solutions for computing optimal resource allocation strategies. The presented solutions are optimal or near-optimal from the perspective of their time complexity. The considered problems have applications in a broad range of domains, like workflow scheduling in industry (e.g. in the mining and metallurgical industry) or the financial sector, motion planning, facility location and data transfer or job scheduling and resource management in Grids, clouds or other distributed systems.
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