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A Multi-objective Optimization Algorithm Based on Tissue P System for VRPTW

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Bio-inspired Computing – Theories and Applications (BIC-TA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 682))

Abstract

Vehicle routing problem with time windows has an important practical significance, but it is NP-Hard problem. In order to solve the problem, an optimization algorithm based on P system is proposed. The encoding of glowworm’s location is considered as evolutionary object and discrete glowworm evolution mechanism and variable neighborhood evolution mechanism are used as sub-algorithms. In this paper, the motion equations and related motion rules of glowworm algorithm are improved to optimize the performance of the algorithm. Meanwhile, in order to enlarge the search area of solution space and improve the precision, the variable neighborhood evolution mechanism is redesigned. Cell communication rules are used to exchange information between cells. Moreover, this paper introduced the concept of Pareto dominance to evaluate the advantages and disadvantages of the object, as a result, this method returns not a single non-dominated solution but a set of no-dominated solutions. At last, by solving the different Solomon numerical examples and simulation results show that the algorithm is easier to jump out of local optimal both achieves very good results in the number of vehicles and distance cost, besides, generates a lot of new solutions which are different from the database. This algorithm has the features of faster convergence rate and accurate precision, and it is competitive with other heuristic or metaheuristic algorithms in the literature.

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Acknowledgments

This project was supported by National Natural Science Foundation of China (Grant No. 61179032), the Special Scientific Research Fund of Food Public Welfare Profession of China(Grant No. 201513004-3) and the Research and Practice Project of Graduate Education Teaching Reform of Wuhan Polytechnic University (YZ2015002).

Author information

Authors and Affiliations

  1. School of Math and Computer, Wuhan Polytechnic University, Wuhan, 430023, Hubei, China

    Wenbo Dong, Kang Zhou & Jun Zhang

  2. Department of Economics and Management, Wuhan Polytechnic University, Wuhan, 430023, Hubei, China

    Huaqing Qi

  3. Key Laboratory of Image Information Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China

    Cheng He

  4. School of Automation, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China

    Bosheng Song

Authors
  1. Wenbo Dong
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  2. Kang Zhou
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  3. Huaqing Qi
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  4. Cheng He
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  5. Jun Zhang
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  6. Bosheng Song
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Corresponding author

Correspondence to Kang Zhou .

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Editors and Affiliations

  1. Xidian University , Xi’an, China

    Maoguo Gong

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. China University of Petroleum, Qingdao, China

    Tao Song

  4. Southwest Jiaotong University , Chengdu, China

    Gexiang Zhang

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© 2016 Springer Nature Singapore Pte Ltd.

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Dong, W., Zhou, K., Qi, H., He, C., Zhang, J., Song, B. (2016). A Multi-objective Optimization Algorithm Based on Tissue P System for VRPTW. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_35

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  • DOI: https://doi.org/10.1007/978-981-10-3614-9_35

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3613-2

  • Online ISBN: 978-981-10-3614-9

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