Abstract
An uncertainty fractional joint probability chance constraint programming is developed to process land use structure optimization under uncertainty. The model integrate uncertainty programming into fractional programming, and the uncertainty programming include interval programming, fuzzy programming, stochastic programming and joint probability chance constraint programming. The results of the study are a series of land use policies in multiple scenarios with interval and deterministic numbers. The advantage of the model include it can (1) effectively integrate the two objectives of economic benefit maximization and pollution minimization by the fractional programming; (2) effectively process the uncertainty by the corresponding uncertainty programming; (3) reflect the impact of uncertainty on system benefit, pollutant discharge, and land use structure policy; and (4) develop a series of possible scenarios and corresponding feasible plans. The results of the study can help planners or decision makers develop flexible land use policy to address the multi-objective problems of maximum, minimum, and uncertainty. The proposed method is universal and can be extended to other cases.
Similar content being viewed by others
References
Arlene E (1995) Uncertainty and forest land use allocation in British Columbia. Mansholt Work Pap 43(4):509–520
Chadha SS, Chadha V (2007) Linear fractional programming and duality. CEJOR 15(2):119–125
Charnes A, Cooper WW (1983) Response to “decision problems under risk and chance constrained programming: dilemmas in the transition”. Manag Sci 29(6):750–753
Chibilev AA, Petrishchev VP, LevykinS V, Ashikkaliev AKh, Kazachkov GV (2016) The soil-ecological index as an integral indicator for the optimization of the land-use structure. Geogr Nat Resour 37(4):348–354
Domptail S, Nuppenau EA (2010) The role of uncertainty and expectations in modeling (range) land use strategies: an application of dynamic optimization modeling with recursion. Ecol Econ 69(12):2475–2485
Emanuela M, Anna B, Massimiliano B, Margherita C, Piermaria C, Luca S (2018) Paths to change: bio-economic factors, geographical gradients and the land-use structure of Italy. Environ Manag 61:116–131
Gao Q, Kang M, Xu H, Jiang Y, Yang J (2010) Optimization of land use structure and spatial pattern for the semi-arid loess hilly–gully region in China. CATENA 81(3):196–202
Gu JJ, Huang GH, Guo P, Shen N (2013) Interval multistage joint-probabilistic integer programming approach for water resources allocation and management. J Environ Manag 128(20):615–624
Gu JJ, Guo P, Huang GH (2016a) Achieving the objective of ecological planning for arid inland river basin under uncertainty based on ecological risk assessment. Stoch Environ Res Risk Assess 30(5):1485–1501
Gu JJ, Mo L, Ping G, Huang GH (2016b) Risk assessment for ecological planning of arid inland river basins under hydrological and management uncertainties. Water Resour Manag 30(4):1415–1431
Gu JJ, Quan Z, Gu D, Zhang Q, Xiao P (2018) The impact of uncertainty factors on optimal sizing and costs of low-impact development: a case study from Beijing, China. Water Resour Manag 32:4217–4238
Guo P, Chen X, Li M, Li J (2014) Fuzzy chance-constrained linear fractional programming approach for optimal water allocation. Stoch Env Res Risk Assess 28(6):1601–1612
Gupta SN (2009) A chance constrained approach to fractional programming with random numerator. J Math Modell Algorithms 8(4):357–360
Jain S, Mangal A, Parihar PR (2011) Solution of fuzzy linear fractional programming problem. OPSEARCH 48(2):129–135
Lai HC, Liu JC, Schaible S (2008) Complex minimax fractional programming of analytic functions. J Optim Theory Appl 137(1):171–184
Lata M, Mittal BS (1976) A decomposition method for interval linear fractional programming. ZAMM J Appl Math Mech 56(4):153–159
Li D (2010) Spatial distribution and characteristics of nitrogen loss in small watershed of three gorges reservoir. Southwest University (in Chinese)
Li X, Ma XD (2017) An uncertain programming model for land use structure optimization to promote effectiveness of land use planning. Chin Geogr Sci 06:130–144
Li X, Ou MH, Liu JS, Yan SQ (2014) Regional land use structure optimization under uncertain theory. Trans Chin Soc Agric Eng 30(4):176–184
Liu Y, Qin X, Guo H, Zhou F, Wang J, Lv X et al (2007) ICCLP: an inexact chance-constrained linear programming model for land-use management of lake areas in urban fringes. Environ Manag 40(6):966–980
Liu Y, Yu Y, Guo H, Yang P (2009) Optimal land-use management for surface source water protection under uncertainty: a case study of Songhuaba Watershed (Southwestern China). Water Resour Manag 23(10):2069–2083
Lu SS, Guan X, Zhou M, Wang Y (2014) Land resources allocation strategies in an urban area involving uncertainty: a case study of Suzhou, in the Yangtze River Delta of China. Environ Manag 53(5):894–912
Lu SS, Zhou M, Guan X, Tao lZ (2015) An integrated GIS-based interval-probabilistic programming model for land-use planning management under uncertainty-a case study at Suzhou, China. Environ Sci Pollut Res 22(6):4281–4296
Luo X, Lu XH, Jin G, Wan Q, Zhou M (2019) Optimization of urban land-use structure in China’s rapidly developing regions with eco-environmental constraints. Phys Chem Earth Parts A B C 110:8–13
Ma SH, Xue MG, Zhou H (2019) A method for planning regional ecosystem sustainability under multiple uncertainties: a case study for Wuhan, China. J Clean Prod 210:1545–1561
Maqsood I, Huang GH, Huang Y, Chen B (2005) ITOM: an interval-parameter two-stage optimization model for stochastic planning of water resources systems. Stoch Env Res Risk A 19(2):125–133
Mehlawat MK, Kumar S (2012) A solution procedure for a linear fractional programming problem with fuzzy numbers. Adv Intell Soft Comput 130:1037–1049
MuñozRojas J, Carrasco RM, De Pedraza J (2009) Regional geomorphology and land-use planning: new possibilities for its application based upon uncertainty and complexity of landforms. The example of the Bullaque River Basin (Toledo Mountain Range, Spain). Boletín de la Real Sociedad Española de Historia Natural, Sección Geológica 103(1–4):23–47
Ou G, Tan S, Zhou M et al (2017) An interval chance-constrained fuzzy modeling approach for supporting land-use planning and eco-environment planning at a watershed level. J Environ Manag 204:651–666
Ren CF, Guo P, Li M, Gu JJ (2013) Optimization of industrial structure considering the uncertainty of water resources. Water Resour Manag 27(11):3885–3898
Ren CF, Li ZH, Zhang HB (2019) Integrated multi-objective stochastic fuzzy programming and AHP method for agricultural water and land optimization allocation under multiple uncertainties. J Clean Prod 210:12–24
Sadeghi S, Jalili K, Nikkami D (2009) Land use optimization in watershed scale. Land Use Policy 26(2):186–193
Singh C, Hanson MA (1991) Multiobjective fractional programming duality theory. Naval Res Logist 38(6):925–933
Wang Q, Wang WM (2012) Uncertainty and land use planning. China Land Science 26(5):88–91 (in Chinese)
Wang H, Gao Y, Liu Q, Song J (2010a) Land use allocation based on interval multi-objective linear programming model: a case study of pi county in Sichuan Province. Chin Geogr Sci 20(2):176–183
Wang SZ, Liu WD, Cao ZY (2010b) Land use quantitative structure optimization based on NSGA-II—a case study of Dinghai District in Zhoushan City. Sci Geogr Sin 30(2):290–294
Wu CF, Shao XZ (2005) A study on the irrational, uncertain and flexible theory of land use planning. J Zhejiang Univ (Human Soc Sci) 35(4):98–105 (In Chinese)
Yang X, Zheng XQ, Lv LN (2012) A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata. Ecol Model 233:11–19
Yang H, Zhang J, Yang Z (2013) Rational land planning utilization structure optimization based on multi-objective linear programming model of Foshan. Advanced Materials Research, pp 616–618
Zhou M (2015) An interval fuzzy chance-constrained programming model for sustainable urban land-use planning and land use policy analysis. Land Use Policy 42:479–491
Zhou M, Tao L, Guan X, Lu S (2015) An integrated GIS-based interval-probabilistic programming model for land-use planning management under uncertainty—a case study at Suzhou, China. Environ Sci Pollut Res Int 22(6):4281–4296
Acknowledgements
We gratefully acknowledge financial supports for this research from projects of National Natural Science Foundation of China (Grant No. 41601581).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that there are no conflict of interest regarding the publication of this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
- \(UB_{i}\) :
-
the benefit of the unit area of the \(i{\text{-}}th\) land use
- \(x_{i}\) :
-
the \(i{\text{-}}th\) type of land use
- \(TN_{i}\) :
-
nitrogen discharge of \(i{\text{-}}th\) type of land use
- \(UI_{i}\) :
-
the invest for \({\text{i-th}}\) type of land use
- \(TI\) :
-
the total governmental invest
- \(UWC_{i}\) :
-
the water requirement for the \(i{\text{-}}th\) type of land use
- \(AWC\) :
-
the water resources of the study area
- \(UP_{i}\) :
-
the population in unit area of the \(i{\text{-}}th\) type of land use
- \(TP\) :
-
the total population of the study area
- \(UL_{i}\) :
-
the amount of labor for the \(i{\text{-}}th\) type of land use
- \(AL\) :
-
the amount of labor in the study area
- \(AA\) :
-
the amount of available area in the study area
- \(MA_{i}\) :
-
the minimum area of the \(i{\text{-}}th\) type of land use of the “planning”
- \(MFCR\) :
-
the minimum requirement of the green spaced ratio
Rights and permissions
About this article
Cite this article
Gu, J., Zhang, X., Xuan, X. et al. Land use structure optimization based on uncertainty fractional joint probabilistic chance constraint programming. Stoch Environ Res Risk Assess 34, 1699–1712 (2020). https://doi.org/10.1007/s00477-020-01841-w
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00477-020-01841-w