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Decentralized Supply Chain Optimization via Swarm Intelligence

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Advances in Swarm Intelligence (ICSI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13344))

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Abstract

When optimised, supply chains can bring tremendous benefits to all its participants. Supply chains therefore can be framed as a networked optimization problem to which swarm intelligence techniques can be applied. Given recent trends of globalization and e-commerce, we propose a supply chain that uses an open e-commerce business model, where all participants have equal access to the market and are free to trade with each other based on mutually agreed prices and quantities. Based on this model, we improve upon the Particle Swarm Optimization algorithm with constriction coefficient (CPSO), and we demonstrate the use of a new random jump algorithm for consistent and efficient handling of constraint violations. We also develop a new metric called the ‘improvement multiplier’ for comparing the performance of an algorithm when applied to a problem with different configurations.

This work is partially supported by the Academia Sinica grant number AS-TP-109-M07 and the Ministry of Science and Technology (Taiwan) grant numbers 107-2118-M-001-011-MY3 and 109-2321-B-001-013.

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References

  1. Singh, K., Lin, S.-P., Phoa, F.K.H., Chen-Burger, Y.-H.J.: Swarm intelligence optimisation algorithms and their applications in a complex layer-egg supply chain. In: Jezic, G., Chen-Burger, J., Kusek, M., Sperka, R., Howlett, R.J., Jain, L.C. (eds.) Agents and Multi-Agent Systems: Technologies and Applications 2021. SIST, vol. 241, pp. 39–51. Springer, Singapore (2021). https://doi.org/10.1007/978-981-16-2994-5_4

    Chapter  Google Scholar 

  2. Corne, D.W., Reynolds, A., Bonabeau, E.: Swarm intelligence. In: Rozenberg, G., Bäck, T., Kok, J.N. (eds.) Handbook of Natural Computing, vol. 2017, no. 6, pp. 1599–1622. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-540-92910-9_48

  3. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN 1995 - International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995)

    Google Scholar 

  4. Kennedy, J., Mendes, R.: Population structure and particle swarm performance. In: Proceedings of the 2002 Congress on Evolutionary Computation (CEC 2002), vol. 2, pp. 1671–1676 (2002)

    Google Scholar 

  5. Kadadevaramath, R.S., Chen, J.C.H., Latha Shankar, B., Rameshumar, K.: Application of particle swarm intelligence algorithms in supply chain network architecture optimization. Expert Syst. Appl. 39(11), 10160–10176 (2012)

    Google Scholar 

  6. Izquierdo, J., Minciardi, R., Montalvo, I., Robba, M. and Tavera, M.: Particle swarm optimization for the biomass supply chain strategic planning. In: Proceedings of iEMSs 2008 - International Congress on Environmental Modelling and Software Integrating Sciences and Information Technology for Environmental Assessment and Decision Making, pp. 1272–1280 (2008)

    Google Scholar 

  7. Sinha, A.K., Aditya, H.K., Tiwari, M.K., Chan, F.T.S.: Agent oriented petroleum supply chain coordination: co-evolutionary particle swarm optimization based approach. Expert Syst. Appl. 38(5), 6132–6145 (2011)

    Article  Google Scholar 

  8. Clerc, M., Kennedy, J.: The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6(1), 58–73 (2002)

    Article  Google Scholar 

  9. Mendes, R., Kennedy, J., Neves, J.: The fully informed particle swarm: simpler, maybe better. IEEE Trans. Evol. Comput. 8(3), 204–210 (2004)

    Article  Google Scholar 

  10. Clerc, M.: Confinements and biases in particle swarm optimization. HAL-00122799 (2006)

    Google Scholar 

  11. Phoa, F.K.H., Chen, R.B., Wang, W.C., Wong, W.K.: Optimizing two-level supersaturated designs via swarm intelligence techniques. Technometrics 58(1), 43–49 (2016)

    Article  MathSciNet  Google Scholar 

  12. Phoa, F.K.H.: A swarm intelligence based (SIB) method for optimization in designs of experiments. Nat. Comput. 16(4), 597–605 (2017)

    Google Scholar 

  13. Phoa, F.K.H., Liu, H.-P., Chen-Burger, Y.-H.J., Lin, S.-P.: Metaheuristic optimization on tensor-type solution via swarm intelligence and its application in the profit optimization in designing selling scheme. In: Tan, Y., Shi, Y. (eds.) ICSI 2021. LNCS, vol. 12689, pp. 72–82. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-78743-1_7

    Chapter  Google Scholar 

  14. Campuzano, F., Mula, J.: Supply Chain Simulation. A System Dynamics Approach for Improving Performance. Springer, London (2011). https://doi.org/10.1007/978-0-85729-719-8

  15. Llaguno, A., Mula, J., Campuzano, F.: State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains. Int. J. Prod. Res. 60(6), 2044–2066 (2022)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Sciences, Heriot-Watt University, Edinburgh, UK

    Karan Singh & Yun-Heh Jessica Chen-Burger

  2. Data Science Degree Program, National Taiwan University, Taipei, Taiwan

    Hsin-Ping Liu

  3. Institute of Statistical Science, Academia Sinica, Taipei, Taiwan

    Frederick Kin Hing Phoa

  4. Institute of Biotechnology, National Taiwan University, Taipei, Taiwan

    Shau-Ping Lin

Authors
  1. Karan Singh
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  2. Hsin-Ping Liu
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  3. Frederick Kin Hing Phoa
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  4. Shau-Ping Lin
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  5. Yun-Heh Jessica Chen-Burger
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Corresponding author

Correspondence to Frederick Kin Hing Phoa .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Shenzhen University, Shenzhen, China

    Ben Niu

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Singh, K., Liu, HP., Phoa, F.K.H., Lin, SP., Chen-Burger, YH.J. (2022). Decentralized Supply Chain Optimization via Swarm Intelligence. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13344. Springer, Cham. https://doi.org/10.1007/978-3-031-09677-8_36

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  • DOI: https://doi.org/10.1007/978-3-031-09677-8_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-09676-1

  • Online ISBN: 978-3-031-09677-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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