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Genetic Algorithm Approach to a Multiobjective Land Allocation Model: A Case Study

Genetic Algorithm Approach to a Multiobjective Land Allocation Model: A Case Study

Gopi Annepu, K. Venkata Subbaiah, N. R. Kandukuri
Copyright: © 2012 |Volume: 3 |Issue: 2 |Pages: 14
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781466610668|DOI: 10.4018/jaeis.2012070106
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MLA

Annepu, Gopi, et al. "Genetic Algorithm Approach to a Multiobjective Land Allocation Model: A Case Study." IJAEIS vol.3, no.2 2012: pp.86-99. http://doi.org/10.4018/jaeis.2012070106

APA

Annepu, G., Subbaiah, K. V., & Kandukuri, N. R. (2012). Genetic Algorithm Approach to a Multiobjective Land Allocation Model: A Case Study. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 3(2), 86-99. http://doi.org/10.4018/jaeis.2012070106

Chicago

Annepu, Gopi, K. Venkata Subbaiah, and N. R. Kandukuri. "Genetic Algorithm Approach to a Multiobjective Land Allocation Model: A Case Study," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 3, no.2: 86-99. http://doi.org/10.4018/jaeis.2012070106

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Abstract

Optimal land allocation plays a vital role for the development of agriculture sector. Development toward optimal utilization of land under cultivation and increasing the production of crops and profit with less fertilizer consumption must be taken into consideration in agriculture planning. In this paper, a weighted additive model is formulated with net profit, production of crops, and fertilizer consumption as objectives and availability of cultivable land, agriculture labour, agriculture machinery, and water as constraints for optimal land allocation. Weighted additive model takes care of relative priority of objectives laid by the agriculture planners. To illustrate the model, a case study of Visakhapatnam district, Andhra Pradesh, India is presented. The results of GA approach are compared with LINGO solver and observed that there is an improvement in the utilization of land.

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