EDP Sciences logo
Submit your paper
Search
Menu
Home All issues Volume 14 (2023) Int. J. Simul. Multidisci. Des. Optim., 14 (2023) 11 References
Open Access
Issue
Int. J. Simul. Multidisci. Des. Optim.
Volume 14, 2023
Article Number 11
Number of page(s) 8
DOI https://doi.org/10.1051/smdo/2023010
Published online 18 October 2023
  1. Y. Zhang, Y. Wang, M. Tang, J. Zhou, T. Zhang, The microbial dark matter and ‘wanted list’ in worldwide wastewater treatment plants, Microbiome 11, 59 (2023) [CrossRef] [Google Scholar]
  2. Y. Chen, Y. Wang, D. Paez-Espino, M.F. Polz, T. Zhang, Prokaryotic viruses impact functional microorganisms in nutrient removal and carbon cycle in wastewater treatment plants, Nat. Commun. 12, 5398 (2021) [CrossRef] [Google Scholar]
  3. S. Sunarsih, P. Purwanto, W. Setia Budi, Modeling of domestic wastewater treatment facultative stabilization ponds, Int. J. Technol. 6, 689–698 (2015) [Google Scholar]
  4. B. Sheng Huang et al., Quantitative study of degradation coefficient of pollutant against the flow velocity, J. Hydrodyn. 29, 118–123 (2017) [CrossRef] [Google Scholar]
  5. B.K. Kogo, E.K. Biamah, P.K. Langat, Optimized design of a hybrid biological sewage treatment system for domestic wastewater supply, J. Geosci. Environ. Prot. 05, 14–29 (2017) [Google Scholar]
  6. A. Gopakumar, R. Narayan, S.A. Nagath, N.P.R. Mohammed, S. Chandran, Waste water treatment using economically viable natural adsorbent materials, Mater. Today Proc. 5, 17699–17703 (2018) [CrossRef] [Google Scholar]
  7. W. Sunarsih, S. Kartono, Mathematical analysis for the optimization of wastewater treatment systems in facultative pond indicator organic matter, E3S Web Conf. 31 (05008), 1–3 (2018) [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  8. D. Recio-Garrido, Y. Kleiner, A. Colombo, B. Tartakovsky, Dynamic model of a municipal wastewater stabilization pond in the arctic, Water Res. 144, 444–453 (2018) [CrossRef] [Google Scholar]
  9. S. Borzooei et al., Optimization of the wastewater treatment plant: from energy saving to environmental impact mitigation, Sci. Total Environ. 691, 1182–1189 (2019) [CrossRef] [Google Scholar]
  10. Z.W. Geem, S.Y. Chung, J.H. Kim, Improved optimization for wastewater treatment and reuse system using computational intelligence, Complexity 2018, 2480365 (2018), doi: 10.1155/2018/2480365 [Google Scholar]
  11. L.T. Ho, A. Alvarado, J. Larriva, C. Pompeu, P. Goethals, An integrated mechanistic modeling of a facultative pond: parameter estimation and uncertainty analysis, Water Res. 151, 170–182 (2019) [CrossRef] [Google Scholar]
  12. D.P. Sunarsih, S. Sasongko. Process improvement on domestic wastewater treatment stabilization ponds by using mathematical optimization approach, MATEMATIKA: MJIAM 35, 171–176 (2019) [CrossRef] [Google Scholar]
  13. M. Jayalakshmi, G. Vijayaraghavan, A. Suresh, Y.T. Hung, Mathematical programming approach for optimal allocation in the wastewater management, Int. J. Environ. Waste Manag. 22, 192–200 (2018) [CrossRef] [Google Scholar]
  14. S.M. Musavi, R. Khosropour, S.A. Musavi, A. Ahmadvand, System dynamics approach for the relationship between different types of hospitals and hospital waste management (case study: Tabriz), Prog. Ind. Ecol., Int. J. 13, 29–41 (2019) [CrossRef] [Google Scholar]
  15. R. Piotrowski, M. Lewandowski, A. Paul, Mixed integer nonlinear optimization of biological processes in wastewater sequencing batch reactor, J. Process. Control. 84, 89–100 (2019) [CrossRef] [Google Scholar]
  16. B. Shomar, K. Al-Darwish, A. Vincent, Optimization of wastewater treatment processes using molecular bacteriology, J. Water Process Eng. 33, 101030 (2020) [CrossRef] [Google Scholar]
  17. D.Y. Yang, D.M. Frangopol, J.G. Teng, Probabilistic life-cycle optimization of durability-enhancing maintenance actions: application to FRP strengthening planning, Eng. Struct. 188, 340–349 (2019) [CrossRef] [Google Scholar]
  18. D. Rakipour, H. Barati, Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response, Energy 173, 384–399 (2019) [CrossRef] [Google Scholar]
  19. D. Tilly, Å. Holm, E. Grusell, A. Ahnesjö, Probabilistic optimization of dose coverage in radiotherapy, Phys. Imaging. Radiat. Oncol. 10, 1–6 (2019) [CrossRef] [Google Scholar]
  20. M. Ourahou, W. Ayrir, A. Haddi, Current correction and fuzzy logic optimizations of Perturb & Observe MPPT technique in photovoltaic panel, Int. J. Simul. Multidisci. Des. Optim. 10, 1–9 (2019) [Google Scholar]
  21. Y.-C. Tsao, V.-V. Thanh, Integrated voltage control and maintenance insurance planning for distribution networks considering uncertainties, Electr. Power Syst. Res. 201, 107501 (2021) [Google Scholar]
  22. S. Emeç, G. Akkaya, Developing a new optimization energy model using fuzzy linear programming, J. Intell. Fuzzy Syst. 40, 9529–9542 (2021) [CrossRef] [Google Scholar]
  23. Y. Ding, Q. Xu, Y. Xia, J. Zhao, X. Yuan, J. Yin, Optimal dispatching strategy for user-side integrated energy system considering multiservice of energy storage, Int. J. Electr. Power Energy Syst. 129, 106810 (2021) [CrossRef] [Google Scholar]
  24. Y.-C. Tsao, V.-V. Thanh, A multi-objective fuzzy robust optimization approach for designing sustainable and reliable power systems under uncertainty, Appl. Soft Comput. J. 92, 106317 (2020), doi: 10.1016/j.asoc.2020.106317 [Google Scholar]
  25. C. Lima, S. Relvas, A. Barbosa-Póvoa, Designing and planning the downstream oil supply chain under uncertainty using a fuzzy programming approach, Comput. Chem. Eng. 151, 107373 (2021), doi: 10.1016/j.compchemeng.2021.107373 [CrossRef] [Google Scholar]
  26. M.K. Sharma et al., A fuzzy optimization technique for multi‐objective aspirational level fractional transportation problem, Symmetry (Basel) 13, 1465 (2021), doi: 10.3390/sym13081465 [Google Scholar]
  27. F. Goodarzian, S.F. Wamba, K. Mathiyazhagan, A. Taghipour, A new bi-objective green medicine supply chain network design under fuzzy environment: hybrid metaheuristic algorithms, Comput. Ind. Eng. 160, 107535 (2021), doi: 10.1016/j.cie.2021.107535 [CrossRef] [Google Scholar]
  28. Y.-C. Tsao, E. Nugraha Ridhwan Amir, V.-V. Thanh, M. Dachyar, Designing an eco-efficient supply chain network considering carbon trade and trade-credit: a robust fuzzy optimization approach, Comput. Ind. Eng. 160, 107595 (2021), doi: 10.1016/j.cie.2021.107595 [Google Scholar]
  29. I.R. Kale, M.A. Pachpande, S.P. Naikwadi, M.N. Narkhede, Optimization of advanced manufacturing processes using socio inspired cohort intelligence algorithm, Int. J. Simul. Multidisci. Des. Optim. 13, 1–8 (2022) [Google Scholar]
  30. W. Sunarsih, S. Kartono, Mathematical analysis for the optimization of wastewater treatment systems in facultative pond indicator organic matter, E3S Web Conf. 31, 1–3 (2018) [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  31. Gubernur DI Yogyakarta (Governor of Special Region Yogyakarta), Surat Keputusan Gubernur Kepala Daerah Istimewa Yogyakarta (Decree of Special Region Yogyakarta Governor) No. 214/KPTS/1991. 1991. [Google Scholar]
  32. M.S. Bazaraa, H.D. Sherali, C.M. Shetty, Nonlinear programming: theory and algorithms (John Wiley & Sons, 2013) [Google Scholar]
  33. B. Liu, Uncertainty theory, in: Springer Uncertainty Research (Springer Berlin Heidelberg, Berlin, Heidelberg, 2015) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.