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Simulation Optimization Approach to Solve a Complex Multi-objective Redundancy Allocation Problem

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Abstract

This chapter addresses the problem of redundancy and reliability allocation in the operational dimensioning of an automated production system. The aim of this research is to improve the global reliability of the system by allocating alternative components (redundancies) that are associated in parallel with each original component. By considering a complex componential approach that simultaneously evaluates the interrelations among subsystems, conflicting goals, and variables of different natures, a solution for the problem is proposed through a multi-objective formulation that joins a multi-objective elitist genetic algorithm with a high-level simulation environment also known as simulation optimization (SIMO) framework.

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Notes

  1. 1.

    Enumerative local search algorithms based on gradients or that use standard techniques of deterministic programming, such as greedy algorithms, or branch and bound techniques [14, 29].

  2. 2.

    The costs of production include

    • CRAMA—cost of the raw materials applied

    • CMPOLl—cost of the manpower of the operation of the line

    • CEEOC—cost of electricity and other combustibles

    • CPSAT—cost of packaging, storing, and transport.

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Acknowledgments

To Dr. Deb and his team at the Kanpur Genetic Algorithms Laboratory (KanGAL) for providing the source code of the MOEA NSGA-II used in this work.

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Authors and Affiliations

  1. Department of Electrical Engineering - DAELT, Federal Technological University of Paraná - UTFPR, Curitiba, PR, Brazil

    Carlos Henrique Mariano

  2. Department of Electrical Engineering - DAELT - Postgraduate Program in Biomedical Engineering, Federal Technological University of Paraná - UTFPR, Curitiba, PR, Brazil

    Carlo Alessandro Zanetti Pece

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  1. Carlos Henrique Mariano
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Correspondence to Carlos Henrique Mariano .

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Editors and Affiliations

  1. Aviation Academy, Amsterdam University of Applied Sciences, Amsterdam, Noord-Holland, The Netherlands

    Miguel Mujica Mota

  2. Facultad de Ingeniería, Universidad Nacional Autónoma de México, Mexico City, Mexico

    Idalia Flores De La Mota

  3. Optimisation Research Group, NICTA, Sydney, New South Wales, Australia

    Daniel Guimarans Serrano

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Mariano, C.H., Pece, C.A.Z. (2015). Simulation Optimization Approach to Solve a Complex Multi-objective Redundancy Allocation Problem. In: Mujica Mota, M., De La Mota, I., Guimarans Serrano, D. (eds) Applied Simulation and Optimization. Springer, Cham. https://doi.org/10.1007/978-3-319-15033-8_2

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