Combining competitive scheme with slack neurons to solve real-time job scheduling problem

Authors:
Ruey-Maw Chen;Shih-Tang Lo;Yueh-Min Huang
Affiliations:
Department of Computer Science and Information Engineering, National Chin-yi Institute of Technology, Taichung 411, Taiwan, ROC;Department of Engineering Science, National Cheng-Kung University, Tainan 701, Taiwan, ROC;Department of Engineering Science, National Cheng-Kung University, Tainan 701, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2007

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Abstract

Generally, how to satisfy the deadline constraint is the major issue in solving real-time scheduling. Recently, neural network using competitive learning rule provides a highly effective method and deriving a sound solution for scheduling problem with less network complexity. However, due to the availability of resources, the machines may not reach full utilization. To facilitate the problem the extra neuron is introduced to the competitive neural network (CHNN). This study tries to impose slack neuron on CHNN with respect to process time and deadline constraints. Simulation results reveal that the competitive neural network imposed on the proposed energy function with slack neurons integrated ensures an appropriate approach of solving this class of scheduling problems of single or multiple identical machines.