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In this paper we consider multiple constrained resource allocation problems,where the constraints can be specified by formulating activity dependencyrestrictions or by using game-theoretic models. All the problems are focused ongeneric resources, with a few exceptions which consider financial resources inparticular. The problems consider low-risk circumstances and the values of theuncertain variables which are used by the algorithms are the expected values ofthe variables. For each of the considered problems we propose novel algorithmicsolutions for computing optimal resource allocation strategies. The presentedsolutions are optimal or near-optimal from the perspective of their timecomplexity. The considered problems have applications in a broad range ofdomains, like workflow scheduling in industry (e.g. in the mining andmetallurgical industry) or the financial sector, motion planning, facilitylocation and data transfer or job scheduling and resource management in Grids,clouds or other distributed systems.

Optimal Constrained Resource Allocation Strategies under Low Risk Circumstances