Genetic search and the dynamic facility layout problem
Computers and Operations Research - Special issue: heuristic, genetic and tabu search
Theory of software reliability based on components
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Software Engineering: A Practitioner's Approach
Software Engineering: A Practitioner's Approach
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
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The modern automation system consists of software and hardware components to achieve the high quality products and processes. In such type of software-based systems, optimal design is more important to improve the system performance. The perfect parameter design problems are complex because of non-linear relationships and interactions may occur among parameters. So, a proper approach is needed for a parameter optimal design. An integrated approach of neural network with genetic algorithms is proposed to address the optimal design of software-based automation system. This article outlines neural network methodology to predict the response of the software-based automation system for various process parameters values. Then, the genetic algorithm is used to predict the quantitative value of process parameter to improve the performance of the system. In this work, a cascading electro-pneumatic kit is taken as case analysis to analyse the performance of software-based system.