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Multi-objective grey wolf optimizer approach to the reliability-cost optimization of life support system in space capsule

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Abstract

The purpose of this paper is to do the reliability-cost optimization of the life support system (LSS) in a space capsule by using a multi-objective gray wolf optimizer algorithm (MOGWO). MOGWO is a population based metaheuristic which mimics the hierarchal & hunting behavior of grey wolves (Canis lupus). An interactive reliability-cost front has been generated by using MOGWO from which decision makers can choose a point of his/her interest. The efficiency of MOGWO in optimizing the reliability-cost of LSS have also been demonstrated by comparing its results with a very popular swarm based optimization technique named multi-objective particle swarm optimization. A framework based upon MOGWO, which is a very new nature inspired metaheuristic, have been presented for reliability-cost optimization of LSS in a space capsule.

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Authors and Affiliations

  1. Department of Mathematics, University of Petroleum and Energy Studies, Dehradun, 248007, India

    Anuj Kumar, Sangeeta Pant & Shshank Chaube

  2. Department of Mathematics, Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, India

    Mangey Ram

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  1. Anuj Kumar
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  2. Sangeeta Pant
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  3. Mangey Ram
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  4. Shshank Chaube
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Correspondence to Mangey Ram.

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Kumar, A., Pant, S., Ram, M. et al. Multi-objective grey wolf optimizer approach to the reliability-cost optimization of life support system in space capsule. Int J Syst Assur Eng Manag 10, 276–284 (2019). https://doi.org/10.1007/s13198-019-00781-1

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