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A Developed NSGA-II Algorithm for Multi-objective Chiller Loading Optimization Problems

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Intelligent Computing Theories and Application (ICIC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9771))

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Abstract

During recent years, for its simplicity and efficiency, the non-dominated-sorting algorithm (NSGA-II) has been widely applied to solve multi-objective optimization problems. However, in the canonical NSGA-II, the resulted population may have multiple individuals with the same fitness values, and which makes the resulted population lack of diversity. To solve this kind of problem, in this study, we propose a developed NSGA-II algorithm (hereafter called NSGA-II-D). In NSGA-II-D, a novel duplicate individuals cleaning procedure is embedded to delete the individuals the same fitness values with other ones. Then, the proposed algorithm is tested on the well-known ZDT1 instance to verify the efficiency and performance. Finally, to solve the realisitc optimization problem in intelligent building system, we select a well-known optimal chiller loading (OCL) problem to test the ability to maintain population diversity. Experimental results on the benchmarks show the efficiency and effectiveness of the proposed algorithm.

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Acknowledgments

This research is partially supported by National Science Foundation of China under Grant 61573178, 61374187 and 61503170, basic scientific research foundation of Northeastern University under Grant N110208001, starting foundation of Northeastern University under Grant 29321006, Science Foundation of Liaoning Province in China (2013020016), Key Laboratory Basic Research Foundation of Education Department of Liaoning Province (LZ2014014), Science Research and Development of Provincial Department of Public Education of Shandong under Grant J12LN39, Shandong Province Higher Educational Science and Technology Program (J14LN28), and Postdoctoral Science Foundation of China (2015T80798, 2014M552040).

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Authors and Affiliations

  1. School of Computer, Liaocheng University, Liaocheng, 252059, China

    Pei-Yong Duan, Yong Wang, Hong-yan Sang, Cun-gang Wang, Min-yong Qi & Jun-qing Li

  2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China

    Jun-qing Li

Authors
  1. Pei-Yong Duan
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  2. Yong Wang
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  3. Hong-yan Sang
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  4. Cun-gang Wang
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  5. Min-yong Qi
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  6. Jun-qing Li
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Corresponding author

Correspondence to Jun-qing Li .

Editor information

Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. Polytechnic of Bari , Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong , North Wollongong, New South Wales, Australia

    Prashan Premaratne

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Duan, PY., Wang, Y., Sang, Hy., Wang, Cg., Qi, My., Li, Jq. (2016). A Developed NSGA-II Algorithm for Multi-objective Chiller Loading Optimization Problems. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_49

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  • DOI: https://doi.org/10.1007/978-3-319-42291-6_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42290-9

  • Online ISBN: 978-3-319-42291-6

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