A hybrid model of multi-objective differential evolution algorithm and various decision-making methods to optimize the batch ABE fermentation process

Document Type : Article


1 Department of Chemical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, P.O. Box 81746-73441, Iran.

2 Department of Chemical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, P.O. Box 71987-74731, Iran.


In recent years, biofuels have attracted considerable attention as renewable and clean source of energy and have been playing the role of suitable alternatives to fossil fuels. One of the most attractive types of biofuels is Acetone-Butanol-Ethanol (ABE) which is produced in a batch fermentation process by the anaerobic bacterium Clostridium acetobutylicum and sugar-based substrate as feedstock. In this paper, optimization of this process was carried out according to a bi-objective function. A hybrid model of Multi-Objective Differential Evolution (MODE) algorithm and distinguished decision-making methods, namely Linear programming technique for Multidimensional Analysis of Preference (LINMAP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Shannon's entropy were applied to find the final optimal operating point. The initial concentration of substrate and the final operating time of the process were selected as decision variables to maximize two main objectives in terms of solvents yield and productivity. A Pareto optimal set presents a wide range of optimal operating points and a proper operating condition can be selected based on the necessities of the applicant. The best optimal point obtained by TOPSIS, according to the lowest value of deviation index, was also compared with the results of economic-based optimization.


Main Subjects

1. Mansur, M.C., O'Donnell, M.K., Rehmann, M.S., and Zohaib, M., ABE Fermentation of Sugar Cane in Brazil, University of Pennsylvania, Department of Chemical and Biomolecular Engineering, Senior Design Reports (CBE) (2010). 2. Votruba, J., Volesky, B., and Yerushalmi, L. Mathematical model of a batch acetone-butanol fermentation", Biotechnol. Bioeng, 28, pp. 247-255 (1986). 3. Jones, D.T. and Woods, D.R. Acetone-butanol fermentation revisited", Microbiol. Rev., 5, pp. 484-524 (1986). 4. Lin, T.Ch. and Lee, Y.H. Modeling and dynamic optimization of semi-batch acetone-butanol-ethanol fermentation with in-situ pervaporation membrane separations", Smart Science, 5(4), pp. 179-193 (2017). 5. Sandu, B., Dobre, T., and Parvulescu, O.C. Modelling and optimization of acetone-butanol-ethanol fedbatch biosynthesis", U.P.B. Sci. Bull., Series B, 76(4), pp. 45-58 (2014). 6. Grisales-Diaz, V.H. and Olivar-Tost, G. Economic optimization of in situ extraction of inhibitors in acetone-ethanol-butanol (ABE) fermentation from lignocellulose", Process Biochemistry, 70, pp. 1-8 (2018). 7. Elmeligy, A., Mehrani, P., and Thibault, J. Arti_cial neural networks as metamodels for the multi-objective optimization of biobutanol production", Appl. Sci., 8(961), pp. 1-16 (2018). 8. Kim, B., Eom, M.H., Jang H., and Lee, J.H. Optimization of the cyclic operation of a continuous biobutanol fermentation process integrated with ex-situ adsorption recovery", IFAC-Papers On Line, 48(8), pp. 1204-1209 (2015). 9. Kim, B., Jang, H., Eom, M.H., and Lee, J.H. Modelbased optimization of cyclic operation of acetonebutanol- ethanol (ABE) fermentation process with exsitu butanol recovery (ESBR) for continuous biobutanol production", Ind. Eng. Chem. Res., 56(8), pp. 2071-2082 (2017). 10. Mariano, A.P., Costa, C.B.B., Angelis, D.F., Filho, F.M., Atala, D.I.P., Maciel, M.R.W., and Filho, R.M. Optimization strategies based on sequential quadratic programming applied for a fermentation process for butanol production", Appl. Biochem. Biotechnol., 159, pp. 366-381 (2009). 11. Mariano, A.P., Costa, C.B.B., Angelis, D.F., Filho, F.M., Atala, D.I.P., Maciel, M.R.W., and Filho, R.M. Optimization of a fermentation process for butanol production by particle swarm optimization (PSO)", J. Chem. Technol. Biotechnol., 85, pp. 934-949 (2010). 12. Sharma, Sh. and Rangaiah, G.P. Multi-objective optimization of a fermentation process integrated with cell recycling and inter-stage extraction", 11th Int. Symposium on Process Systems Engineering, Singapore, pp. 860-864 (2012). 13. Sharif Rohani, A. Multi-objective optimization of butanol production during ABE fermentation", Thesis in Master of Applied Science, University of Ottawa, Canada (2013). 14. Bruns, R.E., Scarminio, I.S., and Neto, B.B., Statistical Design-Chemometrics, 1st Edn., Elsevier, Amsterdam (2006). 15. Bezerra, M.A., Santelli, R.E., Oliveira, E.P., Villar, L.S., and Escaleira, L.A. Response surface methodology (RSM) as a tool for optimization in analytical chemistry", Talanta, 76, pp. 965-977 (2008). 16. Wang, Y. and Blascheck, H.P. Optimization of butanol production from tropical maize stalk juice by fermentation with Clostridium beijerinckii NCIMB 8052", Bioresour. Technol., 102, pp. 9985-9990 (2011). 17. YouSheng, L., Jing, W., XuMing, W., and XiaoHong, S. Optimization of butanol production from corn straw hydrolysate by Clostridium acetobutylicum using M.H. Khademi and S. Zandi Lak/Scientia Iranica, Transactions C: Chemistry and ... 26 (2019) 3401{3414 3413 response surface method", Chinese Sci. Bull., 56, pp. 1422-1428 (2011). 18. Cavazzuti, M., Optimization Methods: From Theory to Design, 1st. Edn., Springer, London (2013). 19. Singh, K.G., Lapsiya, K.L., Gophane, R.R., and Ranade, D.R. Optimization for butanol production using Plackett-Burman design coupled with central composite design by Clostridium beijerenckii strain CHTa isolated from distillery waste manure", J. Biochem. Tech., 7(1), pp. 1063-1068 (2016). 20. Dubey, K.K., Dhingra, A.K., and Rana, Sh. Optimization of process parameters for enhanced biobutanol production from Sargassum wightii hydrolysate", Int. J. Energy Technology and Policy, 11(3), pp. 303- 311 (2015). 21. Kumar, M., Kumar, D., and Singh, B. Utilization of agro residue corncob for production of acetonebutanol using Clostridium acetobutylicum and process optimization through RSM", J. Microbial Biochem. Technol., S8, pp. 1-5 (2014). 22. Zheng, J., Tashiro, Y., Zhao, T., Wang, Q., Sakai, K., and Sonomoto, K. Enhancement of acetone-butanolethanol fermentation from eucalyptus hydrolysate with optimized nutrient supplementation through statistical experimental designs", Renewable Energy, 113, pp. 580-586 (2017). 23. Al-Shorgani, N.K.N., Hamid, A.A., Yuso_, W.M.W., and Kalil, M.S. Pre-optimization of medium for biobutanol production by a new isolate of solventproducing Clostridium", Bioresources, 8, pp. 1420- 1430 (2013). 24. Al-Shorgani, N.K.N., Shukor, H., Abdeshahian, P., Nazir, M.Y.M., Kalil, M.S., Hamid, A.A., and Yuso_, W.M.W. Process optimization of butanol production by Clostridium saccharoperbutylacetonicum N1-4 (ATCC 13564) using palm oil mill e_uent in acetonebutanol- ethanol fermentation", Biocatalysis and Agricultural Biotechnology, 4, pp. 244-249 (2015). 25. Al-Shorgani, N.K.N., Shukor, H., Abdeshahian, P., Nazir, M.Y.M., Kalil, M.S., Yuso_, W.M.W., and Hamid, A.A. Enhanced butanol production by optimization of medium parameters using Clostridium acetobutylicum YM1", Saudi Journal of Biological Sciences, 25(7), pp. 1308-1321 (2018). 26. Khunchantuek, C. and Fiala, K. Optimization of key factors a_ecting butanol production from sugarcane juice by Clostridium beijerinckii TISTR 1461", Energy Procedia., 138, pp. 157-162 (2017). 27. Sirisantimethakom, L., Thanapornsin, T., Laopaiboon, L., and Laopaiboon, P. Enhancement of butanol production e_ciency from sweet sorghum stem juice by Clostridium beijerinckii using statistical experimental design", Chiang Mai J. Sci., 45(3), pp. 1235- 1246 (2018). 28. Pandey, A., Larroche, C., Ricke, S., Dussap, C.-G., and Gnansounou, E. Biofuels. Alternative Feedstocks and Conversion Processes, Academic Press, pp. 571- 582 (2011) 29. Storn, R. and Price, K. Di_erential evolution-A simple and e_cient heuristic for global optimization over continuous spaces", J. Global Optim., 11, pp. 341- 359 (1997). 30. Babu, B.V. and Munawar, S.A. Di_erential evolution strategies for optimal design of shell-and-tube heat exchangers", Chem. Eng. Sci., 62, pp. 3720-3739 (2007). 31. Babu, B.V. and Angira, R. Optimal design of an autothermal ammonia synthesis reactor", Comput. Chem. Eng., 29, pp. 1041-1045 (2005). 32. Babu, B.V. and Angira, R. Modi_ed di_erential evolution (MDE) for optimization of non-linear chemical processes", Comput. Chem. Eng., 30, pp. 989-1002 (2006). 33. Khademi, M.H., Farsi, M., Rahimpour, M.R., and Jahanmiri, A. DME synthesis and cyclohexane dehydrogenation reaction in an optimized thermally coupled reactor", Chemical Engineering and Processing, 50, pp. 113-123 (2011). 34. Khademi, M.H., Rahimpour, M.R., and Jahanmiri, A. Di_erential evolution (DE) strategy for optimization of hydrogen production, cyclohexane dehydrogenation and methanol synthesis in a hydrogen-permselective membrane thermally coupled reactor", International Journal of Hydrogen Energy, 35, pp. 1936-1950 (2010). 35. Khademi, M.H., Setoodeh, P., Rahimpour, M.R., and Jahanmiri, A. Optimization of methanol synthesis and cyclohexane dehydrogenation in a thermally coupled reactor using di_erential evolution (DE) method", International Journal of Hydrogen Energy, 34, pp. 6930-6944 (2009). 36. Khademi, M.H. and Angooraj Taghavi, S. Optimization of ethylene oxychlorination uidized-bed reactor using di_erential evolution (DE) method", Scientia Iranica, 24(3), pp. 1253-1263 (2017). 37. Babu, B.V., Chakole, P.G., and Syed Mubeen, J.H. Multiobjective di_erential evolution (MODE) for optimization of adiabatic styrene reactor", Chemical Engineering Science, 60, pp. 4822-4837 (2005). 38. Hwang, C.L. and Yoon, K., Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, Berlin (1981). 39. Srinivasan, V., Shocker, A.D., and Sethi, S.P. Linear programming techniques for multi-dimensional analysis of preference", Psychometrica, 38, pp. 337-342 (1973). 40. Guisado, J.L., Jimenez Morales, F., and Guerra, J.M. Application of Shannon's entropy to classify emergent behaviors in a simulation of laser dynamics", Math. Comput. Model., 42, p. 847 (2005). 41. Yerushalmi, L., Volesky, B., and Votruba, J. Modelling of culture kinetics and physiology for C. acetobutylicum", Can. J. Chem. Eng., 64, pp. 607-616 (1986). 3414 M.H. Khademi and S. Zandi Lak/Scientia Iranica, Transactions C: Chemistry and ... 26 (2019) 3401{3414 42. Yerushalmi, L., Voleskky, B., and Votruba, J. Fermentation process diagnosis using a mathematical model", Applied Microbiology and Biotechnology, 29, pp. 186-197 (1988). 43. Mulchandani, A. and Volesky, B. Modelling of the acetone-butanol fermentation with cell retention", Canadian J. Chem. Eng., 64, pp. 625-631 (1986). 44. Srivastava, A.K. and Volesky, B. Updated model of the batch acetone-butanol fermentation", Biotechnol. Prog., 12, pp. 693-698 (1990). 45. Vakili, R., Setoodeh, P., Pourazadi, E., Iranshahi, D. and Rahimpour, M.R. Utilizing di_erential evolution (DE) technique to optimize operating conditions of an integrated thermally coupled direct DME synthesis reactor", Chem. Eng. J., 168, pp. 321-332 (2011). 46. Price, K. and Storn, R. Di_erential evolution (DE) for continuous function optimization", Homepage of di_erential evolution as on http://www.ICSI.Berkeley.edu/wstorn/code.html (May 2006). 47. Deb, K., Multi-Objective Optimization Using Evolutionary Algorithms, New York, Wiley (2001). 48. Babu, B.V., Syed Mubeen, J.H., and Chakole, P.G. Simulation and optimization of wiped-_lm polyethylene terephthalate (PET) reactor using multiobjective di_erential evolution (MODE)", Materials and Manufacturing Processes, 22, pp. 541-552 (2007). 49. Li, S.Y., Srivastava, R., Suib, S.L., Li, Y., and Parnas, R.S. Performance of batch, fed-batch, and continuous A-B-E fermentation with pH-control", Bioresour. Technol., 102, pp. 4241-4250 (2011). 50. Nanda, S., Dalai, A. and Kozinski, J. Butanol and ethanol production from lignocellulosic feedstock: biomass pretreatment and bioconversion", Energy Science & Engineering, 2, pp. 138-148 (2014). 51. Yerushalmi, L. and Volesky, B. Culture conditions for growth and solvent biosynthesis by a modi_ed clostridium acetobutylicum", Appl. Microbiol. Biotechnol, 25, pp. 513-520 (1987). 52. Qureshi, N. and Blaschek, H.P. ABE production from corn: a recent economic evaluation", Journal of Industrial Microbiology & Biotechnology, 27, pp. 292- 297 (2001). 53. Kumar, R., Kaushik, S.C., Kumar, R., and Hans, R. Multi-objective thermodynamic optimization of an irreversible regenerative Brayton cycle using evolutionary algorithm and decision making", Ain Shams Eng. J., 7, pp. 741-753 (2016). 54. Sayyaadi, H. and Mehrabipour, R. E_ciency enhancement of a gas turbine cycle using an optimized tubular recuperative heat exchanger", Energy, 38, pp. 362-375 (2012). 55. Etghani, M.M., Shojaeefard, M.H., Khalkhali, A., and Akbari, M. A hybrid method of modi_ed NSGA-II and TOPSIS to optimize performance and emissions of a diesel engine using biodiesel", Appl. Therm. Eng., 59, pp. 309-315 (2013). 56. Ahmadi, M.H., Sayyaadi, H., Dehghani, S., and Hosseinzade, H. Designing a solar powered stirling heat engine based on multiple criteria: maximized thermal e_ciency and power", Energy Convers Manage, 75, pp. 282-291 (2013).