Land-Use Planning for Farming Area in West Java to Divide Allocation of Vegetables Commodity Using Genetic Algorithm Approach
Abstract
This research has created a model to determine the optimum allocation of land-use planning for farming in West Java by considering the two main components, i.e., production and cost. The method is essential in farming, especially in the COVID-19 situation, as it determines clearly which procedure needs to be involved for land-use farming optimization. The problem of land allocation lies in finding the optimum solution from the multi-objective functions. In this study, the method used to cope with the land-use design problem was the Genetic Algorithm (GA) and its expansion called Nondominated Sorting Genetic Algorithm (NSGA). The research results indicated that the best total fitness in GA and NSGA is relatively the same. It was shown that both NSGA and GA could make a planning scheme optimal for the farming commodities in West Java. Based on the maximum optimum value from the best fitness value of NSGA, around 37.35% of the farmland in West Java, it is the best fit for the big red chili commodity. The city where the land used for extensive red chili farming is found to have the maximum optimum value is Garut, with 98.73% of its total farm area.
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References
H. Loedji, “Delapan besar produk pertanian indonesia,” Porto News, 2019.
Central Bank Indonesia., “Laporan Perekonomian Provinsi Jawa Barat,” 2019.
X. Ding, M. Zheng, and X. Zheng, "land The Application of Genetic Algorithm in Land Use Optimization Research: A Review," 2021, DOI: 10.3390/land10050526.
R. Jain and S. K. Srivastava, "Optimization techniques for crop planning: A review Identifying Pathways of Socio-Economic and Socio-Personal Attributes and Study Their Influence on Agricultural Performance across Different Agro-Ecosystems in India View project Regional Crop Planning View project," 2018. [Online]. Available: https://www.researchgate.net/publication/329736318
L. Yaolin, Y. Man, H. Jianhua, and Q. Jing, "Model of land use spatial optimization based on a knowledge guide genetic algorithm," 2015. DOI: 10.1016/J.COMPENVURBSYS.2014.09.002.
M. M. Memmah, F. Lescourret, X. Yao, and C. Lavigne, "Metaheuristics for agricultural land-use optimization. A review," Agronomy for Sustainable Development, vol. 35, no. 3. Springer-Verlag France, pp. 975–998, Jul. 26, 2015. DOI: 10.1007/s13593-015-0303-4.
P. Gao, H. Wang, S. A. Cushman, C. Cheng, C. Song, and S. Ye, "Sustainable land-use optimization using NSGA-II: theoretical and experimental comparisons of improved algorithms," Landscape Ecology, vol. 36, no. 7, pp. 1877–1892, Jul. 2021, DOI: 10.1007/s10980-020-01051-3.
M. Lazoglou, P. Kolokoussis, and E. Dimopoulou, "Investigating the Use of a Modified NSGA-II Solution for Land-Use Planning in Mediterranean Islands," Journal of Geographic Information System, vol. 08, no. 03, pp. 369–386, 2016, DOI: 10.4236/jgis.2016.83032.
J. Bisschop, AIMMS optimization modeling. Lulu. Com, 2006.
T. Pan, Y. Zhang, F. Su, V. Lyne, F. Cheng, and H. Xiao, "Practical, efficient regional land-use planning using constrained multi-objective genetic algorithm optimization," ISPRS International Journal of Geo-Information, vol. 10, no. 2, Feb. 2021, DOI: 10.3390/ijgi10020100.
et al. Liu Y, "Model of land use spatial optimization based on a knowledge guide genetic algorithm," Geo Computation, 2013.
P. Paritosh, B. Kalita, and D. Sharma, "A game theory-based land layout optimization of cities using genetic algorithm," International Journal of Management Science and Engineering Management, vol. 14, no. 3, pp. 155–168, Jul. 2019, DOI: 10.1080/17509653.2018.1505566.
Memmah Mohamed, Lescourret Francoise, Yao Xin, and Lavigne CLaire, “2015_Metaheuristic Land Use_INRA Springer,” Agron Sustain, vol. 35, pp. 975–998, 2015, doi: 10.1007/s13593-015-0303-4.
K. Suthakar, "Multi-objective Optimization for Agricultural Land Uses in the Jaffna Peninsula, Sri Lanka Land suitability evaluation using multi-criteria decision analysis View project," 2018. [Online]. Available: www.ijirk.com
S. Jarin, M. Khaleda Khatun, and A. A. Shafie, "Multi-Objective Constrained Algorithm (MCA) And Non-Dominated Sorting Genetic Algorithm (NSGA-II) For Solving Multi-objective Crop Planning Problem," vol. 11, no. 6, 2016, [Online]. Available: www.arpnjournals.com
V. Sheikh, H. Salmani, A. Salman Mahiny, M. Ownegh, and A. Fathabadi, "Land use optimization through bridging multi-objective optimization and multi-criteria decision-making models (case study: Tilabad Watershed, Golestan Province, Iran)," Natural Resource Modeling, vol. 34, no. 2, May 2021, DOI: 10.1111/nrm.12301.
Cao K, etc., "New 2019_Spatial Multiobjective Land Use Optimizationtoward Livability GA Case Study in Singapore_Journal Geo Cao," International Journal of Geo-Information, vol. 9, no. 40, pp. 1–18, 2020, DOI: 10.3390/ijgi9010040.
H. Mutlu, "Optimization of the multi-objective land-use model with a genetic algorithm," Journal of Design for Resilience in Architecture and Planning, vol. 1, no. 1, pp. 15–32, Dec. 2020, DOI: 10.47818/drarch. 2020.v1i1002.
W. Wang, T. Wu, Y. Li, H. Zheng, and Z. Ouyang, "Matching ecosystem services supply and demand through land-use optimization: A study of the Guangdong-hong Kong-Macao megacity," International Journal of Environmental Research and Public Health, vol. 18, no. 5, pp. 1–15, Mar. 2021, DOI: 10.3390/ijerph18052324.
K. Huang, X. Liu, X. Li, J. Liang, and S. He, "An improved artificial immune system for seeking the Pareto front of land-use allocation problem in large areas," International Journal of Geographical Information Science, vol. 27, no. 5, pp. 922–946, May 2013, DOI: 10.1080/13658816.2012.730147.
Z. Saing, H. Djainal, and S. Deni, "Land use balance determination using satellite imagery and geographic information system: case study in South Sulawesi Province, Indonesia," Geodesy and Geodynamics, vol. 12, no. 2, pp. 133–147, Mar. 2021, doi: 10.1016/j.geog.2020.11.006.
V. Sheikh, H. Salmani, A. Salman Mahiny, M. Ownegh, and A. Fathabadi, "Land use optimization through bridging multi-objective optimization and multi-criteria decision-making models (case study: Tilabad Watershed, Golestan Province, Iran)," Natural Resource Modeling, vol. 34, no. 2, May 2021, DOI: 10.1111/nrm.12301.
Kobayashi Y, Higa M, Higashiyama K, and Nakamura F, "2020_Driversofland-usechangesinsocietieswithdecreasingpopulations-Japan_PLOS ONE," PLoS ONE, Jul. 2020, DOI: https://doi.org/10.371/journal.pone.0235846.
Subiyanto, Hermanto, Arief U M, and Nafi a Y, "New 2018_An accurate assessment tool based on the intelligent technique for suitability of soybean cropland_ case study in Kebumen Indonesia _ Elsevier Enhanced Reader," Elsevier, 2018, DOI: https://doi.org/10.1016/j.heliyon.2018.e00684.
E. Ustaoglu, M. E. Kabadayi, and P. J. Gerrits, "The estimation of non-irrigated crop area and production using the regression analysis approach: A case study of Bursa Region (Turkey) in the mid-nineteenth century," PLoS ONE, vol. 16, no. 4 April, Apr. 2021, DOI: 10.1371/journal.pone.0251091.
S. Safitri, K. Wikantika, A. Riqqi, A. Deliar, and I. Sumarto, "Spatial allocation based on physiological needs and land suitability using the combination of ecological footprint and SVM (case study: Java Island, Indonesia)," ISPRS International Journal of Geo-Information, vol. 10, no. 4, Apr. 2021, DOI: 10.3390/ijgi10040259.
A Hardanto, Ardiansyah, and A Mustofa, "New_2021_Crop stage classification using supervised algorithm_Hardanto ICSARD 2020," IOP Conf. Series: Earth and Environmental Science, p. 653, 2021, DOI: 10.1088/1755-1315/653/1/012102.
B. Feizizadeh, D. Omarzadeh, M. Kazemi Garajeh, T. Lakes, and T. Blaschke, "Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine," Journal of Environmental Planning and Management, 2021, DOI: 10.1080/09640568.2021.2001317.
Shikur Habte Z, "2020_Agricultural policies, agricultural production and rural households' welfare in Ethiopia_Journal of Economic Structures," Journal of Economic Structures, vol. 9, 2020, DOI: https://doi.org/10.1186/s40008-020-00228-y.
Mora O, etc., "New 2020_Exploring the future of land use and food security_ A new set of global scenarios _ PLOS ONE," PLOS ONE, vol. 15, no. 7, 2020, DOI: https://doi.org/10.1371/journal.pone.0235597.
M. M. Rahman and G. Szabó, "Multi-objective urban land use optimization using spatial data: A systematic review," Sustainable Cities and Society, vol. 74. Elsevier Ltd, Nov. 01, 2021. DOI: 10.1016/j.scs.2021.103214.
Q. Li et al., "Firefly algorithm-based cellular automata for reproducing urban growth and predicting future scenarios," Sustainable Cities and Society, vol. 76, Jan. 2022, DOI: 10.1016/j.scs.2021.103444.
Palupi I, Wahyudi B.A, and Saadah S, "New 2021_Optimization of Crops Allocation Planning in Cianjur Involving Water Cost Constraints Using Genetic Algorithm," 9th International Conference on Information and Communication Technology (IC0ICT), 2021, DOI: 10.1109/ICoICT52021.2021.9527509.
N. Srinivas and K. Deb, "Multi-objective optimization using nondominated sorting in genetic algorithms. Evolutionary computation," Evolutionary Computation, vol. 2, no. 3, pp. 221–248, 1994.
S. Prakash and D. P. Vidyarthi., "Maximizing availability for task scheduling in the computational grid using genetic algorithm.," Concurrency and Computation: Practice and Experience, vol. 27, no. 1, pp. 193–210, 2015.
I. Berlianty and M. Arifin., Teknik optimasi heuristik. Yogyakarta: Graha Ilmu, 2010.
S. A. A. P. and T. M. K. Deb, "A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II," Springer-In International conference on parallel problem solving from nature, pp. 849–858, 2000.
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