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2000

A neural network approach for a robot task sequencing problem

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A neural network approach for a robot task sequencing problem
This paper presents a neural network approach with successful implementation for the robot task-sequencing problem. The problem addresses the sequencing of tasks comprising loading and unloading of parts into and from the machines by a material-handling robot. The performance criterion is to minimize a weighted objective of the total robot travel time for a set of tasks and the tardiness of the tasks being sequenced. A three-phased parallel implementation of the neural network algorithm on Thinking Machine's CM-5 parallel computer is also presented which resulted in a dramatic increase in the speed of finding solutions. To evaluate the performance of the neural network approach, a branch-and-bound method and a heuristic procedure have been developed for the problem. The neural network method is shown to give good results and is especially useful for solving large problems on a parallel-computing platform. 2000 Elsevier Science Ltd. All rights reserved.
Oded Maimon, Dan Braha, Vineet Seth
Added 17 Dec 2010
Updated 17 Dec 2010
Type Journal
Year 2000
Where AEI
Authors Oded Maimon, Dan Braha, Vineet Seth
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