Abstract
References
- Babalola, M. A. (2015). A multi-criteria decision analysis of waste treatment options for food and biodegradable waste management in japan. Environments. 2(4): 471-488.
- Chinneck, J. W. (2006). Practical optimization: a gentle introduction. Systems and Computer Engineering), Carleton University, Ottawa. http://www. sce. carleton. ca/faculty/chinneck/po. html.
- Hamby, D. (1994). A review of techniques for parameter sensitivity analysis of environmental models. Environmental monitoring and assessment. 32(2): 135-154.
- Helton, J., Iman, R., Johnson, J. and Leigh, C. (1986). Uncertainty and sensitivity analysis of a model for multicomponent aerosol dynamics. Nuclear technology. 73(3): 320-342.
- Hillier, F. S. (2012). Introduction to operations research. Tata McGraw-Hill Education.
- Iman, R. L. and Helton, J. C. (1988). An investigation of uncertainty and sensitivity analysis techniques for computer models. Risk analysis. 8(1): 71-90.
- Lyeme, H. A., Mushi, A. and Nkansah-Gyekye, Y. (2016). Multi-objective optimization model formulation for solid waste management in dar es salaam, tanzania. Asian Journal of Mathematics and Applications. 2017.
- Provsek, A. and Leskovar, M. (2015). Use of fast fourier transform for sensitivity analysis. http:cdn.intechopen.com/pdfs-wm/48177.pdf. Accessed on 10 November 2016.
- Vanderbei, R. J. et al. (2015). Linear programming. Springer.
Sensitivity analysis of multi-objective optimization for solid waste management: A case study of Dares Salaam, Tanzania
Abstract
In this study, a sensitivity analysis of a
multi-objective optimization model for solid waste management (SWM) for Dar es
Salaam city in Tanzania is considered. Our objectives were to identify the most
sensitive parameters and effect of other input data to the model output. Five
scenarios were considered by varying their associated parameter values. The
results showed that the decrease of total cost for the SWM system in all
scenarios was observed compared to the baseline solution when the single
landfill was considered. Furthermore, the analysis shows that the variable cost
parameter for the processing facilities is very sensitivity in such a way that
if you increase the variable cost then, there is a rapid increase of total cost
for the SWM system and the vice versa is true. The relevant suggestions to the
decision makers were also discussed.
References
- Babalola, M. A. (2015). A multi-criteria decision analysis of waste treatment options for food and biodegradable waste management in japan. Environments. 2(4): 471-488.
- Chinneck, J. W. (2006). Practical optimization: a gentle introduction. Systems and Computer Engineering), Carleton University, Ottawa. http://www. sce. carleton. ca/faculty/chinneck/po. html.
- Hamby, D. (1994). A review of techniques for parameter sensitivity analysis of environmental models. Environmental monitoring and assessment. 32(2): 135-154.
- Helton, J., Iman, R., Johnson, J. and Leigh, C. (1986). Uncertainty and sensitivity analysis of a model for multicomponent aerosol dynamics. Nuclear technology. 73(3): 320-342.
- Hillier, F. S. (2012). Introduction to operations research. Tata McGraw-Hill Education.
- Iman, R. L. and Helton, J. C. (1988). An investigation of uncertainty and sensitivity analysis techniques for computer models. Risk analysis. 8(1): 71-90.
- Lyeme, H. A., Mushi, A. and Nkansah-Gyekye, Y. (2016). Multi-objective optimization model formulation for solid waste management in dar es salaam, tanzania. Asian Journal of Mathematics and Applications. 2017.
- Provsek, A. and Leskovar, M. (2015). Use of fast fourier transform for sensitivity analysis. http:cdn.intechopen.com/pdfs-wm/48177.pdf. Accessed on 10 November 2016.
- Vanderbei, R. J. et al. (2015). Linear programming. Springer.
Details
| Primary Language | English |
|---|---|
| Journal Section | Research Article |
| Authors | |
| Publication Date | October 1, 2017 |
| Published in Issue | Year 2017 Volume: 5 Issue: 4 |