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Parallel–Series System Optimization by Weighting Sum Methods and Nature-Inspired Computing

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Applied Nature-Inspired Computing: Algorithms and Case Studies

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

Optimization of systems at the design stage is a key element for competitive industrial installations and plants. The subsystems of a system may be connected in various structural configurations such as in series, parallel–series, and bridge networks. The design of such systems involves challenges of reliability, cost, availability, weight, and volume. Often, in the literature, this optimization problem is addressed as a single-objective one. This chapter investigates the design of a parallel–series system by considering both the system cost and availability as objectives. The multi-objective optimization problem is converted into a single-objective problem using two weighed sum methods. Numerical results of five nature-inspired computing techniques are compared in order to highlight their performances in solving this problem. These are the genetic algorithm (GA), differential evolution (DE), particle swarm optimization (PSO), the flower pollination algorithm (FPA), and the plant propagation algorithm (PPA).

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Author information

Authors and Affiliations

  1. LMSS, Faculty of Engineering Sciences, M’Hamed Bougara University, Boumerdes, Algeria

    Mohamed Arezki Mellal

  2. Department of Mathematical Sciences, University of Essex, Colchester, UK

    Abdellah Salhi

Authors
  1. Mohamed Arezki Mellal
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  2. Abdellah Salhi
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Correspondence to Mohamed Arezki Mellal .

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Editors and Affiliations

  1. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  2. Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

  3. Research and Development and Academic Affairs, RCC Institute of Information Technology, Kolkata, India

    Siddhartha Bhattacharyya

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Mellal, M.A., Salhi, A. (2020). Parallel–Series System Optimization by Weighting Sum Methods and Nature-Inspired Computing. In: Dey, N., Ashour, A., Bhattacharyya, S. (eds) Applied Nature-Inspired Computing: Algorithms and Case Studies. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-13-9263-4_10

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