Optimal task assignment using a neural network
説明
Summary form only given. A neural network is described that solves the problem of optimally assigning tasks to processors in a message-passing parallel machine. This task assignment problem (TAP) is defined by creating a task assignment cost function that expresses the cost of communication overhead and load imbalance. TAP is a kind of combinatorial optimization problem which can be solved efficiently by using a neural network, but the Hopfield and Tank approach has certain limitations. The authors have solved these two problems by use of an improved Hopfield model network. By representing TAP in a more direct manner in the neural network, the need for constraints is eliminated, a valid solution is guaranteed, and the number of neurons and connections needed is reduced substantially. >
収録刊行物
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- International 1989 Joint Conference on Neural Networks
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International 1989 Joint Conference on Neural Networks 591 vol.2-, 1989-01-01
IEEE
