Multicriterial optimization strategies for electron beam grafting of corn starch

  • 1 University of Chemical Technology and Metallurgy, Bulgaria
  • 2 University of Chemical Technology and Metallurgy, Bulgaria; Institute of Electronics, Bulgarian Academy of Sciences, Bulgaria
  • 3 National Institute for Lasers, Plasma and Radiation Physics, Electron Accelerators Laboratory, Romania


Grafting is the most effective way of modifying and regulating the properties of natural polysaccharides for the production of highly efficient graft copolymers, which have applications as flocculating agents for the treatment of different wastewaters. An experimental investigation connected with the modification of starch by grafting acrylamide with the application of electron beam irradiat ion is performed. In this paper the implementation of different multi-criteria optimization strategies, solving the problem with the choice between several compromise Pareto-optimal solutions are presented and compared for the process of electron beam grafting of corn starch. The compromise Pareto-optimal solutions are obtained by implementation of genetic algorithm and a set of requirements for the desired reference direction (minimum or maximum) and the constraints of the investigated quality characteristics and their variances under production conditions, which ensure the fulfilment of several goals – economic efficiency, assurance of low toxicity and high copolymer efficiency in flocculation process.



  1. G. Craciun, E. Manaila, M. Niculescu, D. Ighigeanu, Polym. Bull. 1299 (2017)
  2. M. R. Nemţanu, M. Braşoveanu, Polymer science: research advances, practical applications and educational aspects, ed. A Méndez-Vilas and A. Solano-Martín (Badajoz: Formatex Research Center) 270-277 (2016)
  3. M. Braşoveanu, L. St. Ko leva, M. R. Nemţanu, E. G. Ko leva, T. P. Paneva. J. of Phys.: Conf. Ser., 1089 (2018)
  4. L. Koleva, E. Koleva, M. Nemtanu, M. Braşoveanu, Inter. Sci. J. of Sci. Tech. Union of Mech. Eng. "Industry 4.0", 4, 2, 48-51 (2019)
  5. E. Koleva, I. Vuchkov, Vacuum, 77, 423-428 (2005)
  6. I. N. Vuchkov, L. N. Boyadjieva, Quality improvement with design of experiments (The Netherlands, Kluwer Academic Publishers, 2001)
  7. S. Najafi, A. Salmasnia, R. B. Kazemzadeh, AJBAS, 5/9, 1566-1577 (2011)
  8. QstatLab home page:
  9. S. Stoyanov, Bioautomation, 13(2), 1-18 (2009)

Article full text

Download PDF