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Scheduling multi-objective open shop scheduling using a hybrid immune algorithm

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Abstract

Despite their importance, hardly ever have multi-objective open shop problems been the topic of researches. This paper studies the mentioned problem and proposes some novel multi-objective solution methods centered on the idea behind artificial immune and simulated annealing algorithms incorporating with powerful and fast local search engines. First, the algorithms are tuned and then carefully evaluated for their performance by means of multi-objective performance measures and statistical tools. An available ant colony optimization is also brought into the experiment. Among the proposed algorithms, the results show that the variant of enhanced artificial immune algorithm outperforms the others.

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Authors and Affiliations

  1. Young Researchers Club, Islamic Azad University, Qazvin Branch, Qazvin, Iran

    B. Naderi

  2. Department of Business Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran

    M. Mousakhani

  3. Department of Industrial Engineering, Islamic Azad University, Karaj Branch, Karaj, Iran

    M. Khalili

Authors
  1. B. Naderi
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  2. M. Mousakhani
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  3. M. Khalili
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Correspondence to B. Naderi.

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Naderi, B., Mousakhani, M. & Khalili, M. Scheduling multi-objective open shop scheduling using a hybrid immune algorithm. Int J Adv Manuf Technol 66, 895–905 (2013). https://doi.org/10.1007/s00170-012-4375-x

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  • DOI: https://doi.org/10.1007/s00170-012-4375-x

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