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Industrial Symbioses: Bi-objective Model and Solution Method

  • Sophie Hennequin
  • Vinh Thanh HoEmail author
  • Hoai An Le Thi
  • Hajar Nouinou
  • Daniel Roy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)

Abstract

The concept of industrial symbiosis is interesting because it allows a significant waste reuse. Indeed, when an enterprise cannot more reduce its wastes nor reuse, it may be beneficial to sell those wastes to other factories for which they will be raw materials. However, to achieve this, it is important to be able to firstly, group complementary enterprises in a same area and secondly, ensure an economic gain to each involved enterprises and a global ecologic gain for the considered area/region. Then, we face a bi-objective problem in which objectives could be conflicting and address this issue, propose a solution to mathematically model this problem and propose a way to solve it. Finally, we will apply this model and its resolution to a real study case located in China.

Keywords

Industrial symbiosis Mathematical modeling Linear scalarization ϵ-constraint Waste management 

References

  1. 1.
    Barnosky, A.D., Hadly, E.A., Bascompte, J., Berlow, E.L., Brown, J.H., Fortelius, M., Getz, W.M., Harte, J., Hastings, A., Marquet, P.A., Martinez, N.D., Mooers, A., Roopnarine, P., Vermeij, G., Williams, J.W., Gillespie, R., Kitzes, J., Marshall, C., Matzke, N., Mindell, D.P., Revilla, E., Smith, A.B.: Approaching a state shift in Earth’s biosphere. Nature 486, 52–58 (2012)Google Scholar
  2. 2.
    Frosch, R.: Industrial ecology: a philosophical introduction. Proc. Natl. Acad. Sci. USA 89, 800–803 (1992)Google Scholar
  3. 3.
    Ayres, R.U.: Industrial Metabolism in Technology and Environment (1989)Google Scholar
  4. 4.
    Trevisan, M., Nascimento, L.F., Madruga, L.R.D.R.G., Mülling, D.N., Figueiró, P.S., Bossle, M.B.: Industrial ecology, industrial symbiosis and industrial Eco-parc: to know to apply. Syst. Manag. 11, 204–215 (2016)Google Scholar
  5. 5.
    Wiecek, M.M., Ehrgott, M., Engau, A.: Continuous multiobjective programming. In: Multiple Criteria Decision Analysis, pp. 739–815. Springer, New York (2016)Google Scholar
  6. 6.
    Ehrgott, M.: A discussion of scalarization techniques for multiple objective integer programming. Ann. Oper. Res. 147(1), 343–360 (2006)Google Scholar
  7. 7.
    Hwang, C.-L., Masud, A.S.M.: Multiple Objective Decision Making, Methods and Applications: A State-of-the-Art Survey. Springer-Verlag (1979)Google Scholar
  8. 8.
    Mavrotas, G.: Effective implementation of thee-constraint method in multi-objective mathematical programming problems. Appl. Math. Comput. 213, 455–465 (2009)Google Scholar
  9. 9.
    Miettinen, K.: Nonlinear Multiobjective Optimization. Springer (1999)Google Scholar
  10. 10.
    Holzmann, T., Smith, J.C.: Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations. Eur. J. Oper. Res. 271, 436–449 (2018)Google Scholar
  11. 11.
    Chertow, M.R.: Industrial symbiosis: literature and taxonomy. Ann. Rev. Energy Environ. 25, 313–337 (2000)Google Scholar
  12. 12.
    Li, B., Xiang, P., Hu, M., Zhang, C., Dong, L.: The vulnerability of industrial symbiosis: a case study of Qijiang Industrial Park China. J. Cleaner Prod. 157, 267–277 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Sophie Hennequin
    • 1
  • Vinh Thanh Ho
    • 1
    Email author
  • Hoai An Le Thi
    • 1
  • Hajar Nouinou
    • 1
  • Daniel Roy
    • 1
  1. 1.LGIPMUniversity of LorraineMetzFrance

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