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A multi-objective optimization method based on discrete bacterial algorithm for environmental/economic power dispatch

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An Erratum to this article was published on 22 April 2017

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Abstract

Multi-objective optimization is an interesting and hot topic in the literature involving the conflicting objectives to be solved simultaneously. In this study, a new multiple optimization method based on a discrete bacterial algorithm is developed to address the multi-objective economic-environmental dispatch problem with non-linear, non-convex, and complexity constraints. In the proposed multi-objective bacterial based algorithm, the existence of bacteria complies with a fitness survival mechanism, in which a health sorting approach is operated to control the chances of reproduction as well as elimination. The performances of bacteria have been recorded and sorted for health evaluation, which can help to group the individuals according to their search capability and improve the overall quality of the population. To speed up the convergence rate and avoid local minima to some extent, a comprehensive learning strategy is embedded to enable the communication exchanges between the bacteria and external archive. The standard IEEE 30-bus, 6-generator test system is adopted to illustrate the efficiency of the proposed method by making the comparison with the other multiple bacterial-based algorithms as well as six other well developed evolutionary algorithms. The effectiveness of the propose method is well validated in experiments by providing similar or superior solutions to environmental/economic power dispatch issues considering the various constraints.

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  • 22 April 2017

    An erratum to this article has been published.

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Acknowledgements

This work is partially supported by The National Natural Science Foundation of China (Grants Nos. 71571120, 71001072, 71271140) and Humanity, Social Science Youth Foundation of Ministry of Education of China (16YJC630153), Natural Science Foundation of Guangdong Province (2016A030310074) and Shenzhen Science and Technology Plan (CXZZ20140418182638764). The authors also would like to thank The Hong Kong Polytechnic University Research Committee for financial and technical support.

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    Authors and Affiliations

    1. Department of Business Management, Shenzhen Institute of Information Technology, Shenzhen, 518172, China

      Lijing Tan

    2. College of Management, Shenzhen University, Shenzhen, 518060, China

      Hong Wang, Chen Yang & Ben Niu

    3. Faculty of Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

      Hong Wang

    4. School of Computing, Information, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA

      Ben Niu

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    1. Lijing Tan
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    2. Hong Wang
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    3. Chen Yang
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    4. Ben Niu
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    Correspondence to Chen Yang or Ben Niu.

    Additional information

    An erratum to this article is available at https://doi.org/10.1007/s11047-017-9623-4.

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    Tan, L., Wang, H., Yang, C. et al. A multi-objective optimization method based on discrete bacterial algorithm for environmental/economic power dispatch. Nat Comput 16, 549–565 (2017). https://doi.org/10.1007/s11047-017-9620-7

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