ANN Based Grid Computing to Improve Job Shop Scheduling Process with Advanced Metrics

The field of engineering tried to solve the Job Shop Scheduling Problem (JSSP) for years together. Many models and algorithms were developed to solve it. Mostly the models were limited to production and maintenance systems. The main implementations were in the field of automobile engineering. This paper aims to solve the JSSP problem that can be applied to the field of computers. Recently Artificial Neural Network (ANN) have been applied to solve them. The importance was given only to the scheduling/sequencing of the jobs, so as to minimize the floating time of the jobs. The main contribution of the paper is an improvement of the model proposed in the literatures. The aim is to implement the problem in Grid Computing so as to improve its performance. Along with the Grid Computing which has heuristics in it, Neural Network is also used. Along with this data files and databases are used. This combination will provide a good result when it is implemented using a Mobile Agent called Aglet. This enhances its performance.