Graphs and algorithms
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Look-ahead techniques for micro-opportunistic job shop scheduling
Look-ahead techniques for micro-opportunistic job shop scheduling
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Resource Allocation Optimization for GSD Projects
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part II
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In this paper we describe an approach to allocating a set of tasks to a set of resources or processors. The novelty of the approach has to do with the way decisions are performed. Rather than making one decision about one resource (or one task) at a time, several decisions concerning multiple resources and multiple tasks are made at a time. The algorithm incorporates the formulation of the assignment problem. Furthermore, knowledge about temporal constraints between activities is exploited to improve the computational efficiency of the algorithm. The algorithm is very flexible, allowing for the incorporation of different types of constraints as well as the consideration of non-equivalent resources.