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Process Plan and Scheduling Integration for Near Optimal Process Plans in Networked Based Manufacturing Using Controlled Elitist NSGA-II and Territory Defining Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7677))

Abstract

The networked based manufacturing offers various advantages in current competitive atmosphere by way to reduce the short manufacturing cycle time and to maintain the production flexibility. In this paper, we have addressed a multi-objective problem whose objectives are to minimize the makespan and maximization of machine utilization for generating feasible process plans of multiple jobs in the context of networked based manufacturing system. In more specific, with two powerful multi-objective evolutionary algorithms (MOEAs) namely controlled elitist-NSGA-II (CE-NSGA-II), and territory defining evolutionary algorithm (TDEA), were proposed to find the better performance of the system. With the help of an illustrative example along with two complex scenarios these algorithms has been implemented, tested and compared. Finally, the computational results are analyzed to the benefit of the manufacturer.

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© 2012 Springer-Verlag Berlin Heidelberg

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Manupati, V.K., Thakkar, J.J., Mohapatra, P., Kumar, A., Tiwari, M.K. (2012). Process Plan and Scheduling Integration for Near Optimal Process Plans in Networked Based Manufacturing Using Controlled Elitist NSGA-II and Territory Defining Algorithms. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_88

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  • DOI: https://doi.org/10.1007/978-3-642-35380-2_88

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35379-6

  • Online ISBN: 978-3-642-35380-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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