Design of Adaptive Neural Network Algorithm for Superior Job-Shop Scheduling

International Journal of Mechanical Engineering

© 2016 by SSRG - IJME Journal

Volume 3 Issue 3

Year of Publication : 2016

Authors : Dr. J. Sathish Reddy, V.Manishvarma

10.14445/23488360/IJME-V3I3P102

How to Cite?

Dr. J. Sathish Reddy, V.Manishvarma, "Design of Adaptive Neural Network Algorithm for Superior Job-Shop Scheduling," SSRG International Journal of Mechanical Engineering, vol. 3,  no. 3, pp. 1-5, 2016. Crossref, https://doi.org/10.14445/23488360/IJME-V3I3P102

Abstract:

Artificial Neural Networks are moderately crude electronic models based on the neural structure of the brain. The brain modeling permits less technical approach to create machine solutions. This novel approach used to calculating as well provides a more graceful degradation during system overload than its more traditional counterparts. Artificial Neural Networks can realize higher end computation rates by way of employing anenormous number of smooth processing elements with a large number of connectivity between elements. In this paper an effort is made to provide a Constraint Satisfaction Adaptive Neural Network (CSANN) to solve the global jobshop scheduling problem and it expressions how to manage a difficult constraint satisfaction job-shop scheduling problem onto a simple neural net, somewhere the amount of neural processors equals the amount of operations, and the number of interconnections propagates linearly with the total number of operations. The proposed technique is used to easily construct the neural networks and can alter its weights of network connection based on the sequence and sourceconstrictions of the job-shop scheduling problem during its processing. SLAM Simulation language used to simulate the proposed neural network and produce good solutions for jobshop scheduling problem.

Keywords:

Job-Shop Scheduling, Artificial Neural Networks,Constraint Satisfaction Adaptive Neural Network, SLAM Simulation language, Learning Capability, Priority rules.

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