Integrated aggregate supply chain planning using memetic algorithm – A performance analysis case study. Fahimnia, B., Farahani, R., & Sarkis, J. International Journal of Production Research, 51(18):5354--5373, 2013.
Integrated aggregate supply chain planning using memetic algorithm – A performance analysis case study [link]Paper  doi  abstract   bibtex   
This paper aims to examine how a complex supply chain yields cost reduction benefits through the global integration of production and distribution decisions. The research is motivated by a complex real world supply chain planning problem facing a large automotive company. A mixed-integer nonlinear production-distribution planning model is solved using a customised memetic algorithm. The performance and effectiveness of the developed model and solution approach in achieving the global optimisation is investigated through experiments comparing the numerical results from the proposed integrated approach with those of a typical non-integrated (hierarchical) production–distribution optimisation.
@article{ fahimnia_integrated_2013,
  title = {Integrated aggregate supply chain planning using memetic algorithm – {A} performance analysis case study},
  volume = {51},
  issn = {0020-7543},
  url = {http://www.tandfonline.com/doi/abs/10.1080/00207543.2013.774492},
  doi = {10.1080/00207543.2013.774492},
  abstract = {This paper aims to examine how a complex supply chain yields cost reduction benefits through the global integration of production and distribution decisions. The research is motivated by a complex real world supply chain planning problem facing a large automotive company. A mixed-integer nonlinear production-distribution planning model is solved using a customised memetic algorithm. The performance and effectiveness of the developed model and solution approach in achieving the global optimisation is investigated through experiments comparing the numerical results from the proposed integrated approach with those of a typical non-integrated (hierarchical) production–distribution optimisation.},
  number = {18},
  urldate = {2013-09-23TZ},
  journal = {International Journal of Production Research},
  author = {Fahimnia, B. and Farahani, R.Z. and Sarkis, J.},
  year = {2013},
  pages = {5354--5373}
}

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