scholarly journals Optimized allocation of cultivated land in land consolidation project area based on multi-objective linear programming

2019 ◽  
Vol 34 (4) ◽  
pp. 718
Author(s):  
Bo HAN ◽  
Xiao-bin JIN ◽  
Rui SUN ◽  
Xiao-min XIANG ◽  
Jing LIU ◽  
...  
Author(s):  
Esra Kaplan ◽  
Hayriye Sibel Gülse Bal

Land consolidation is a powerful and effective tool in solving the fragmentation problem of agricultural lands to form a larger, more rational and efficient land for the farmers. The benefits of land consolidation projects are providing access to parcels, efficient use of water resources, real location of parcels, and reducing the costs of irrigation and drainage projects. Although not sufficiently successful, the land consolidation projects in Turkey had been initiated in 1961. This study was aimed to measure and assess the knowledge, expectation and attitudes of farmers on the land consolidation project planned to be implemented for some villages in Artova District of Tokat Province, Turkey. The study was carried out in Taşpınar and Aşağı Güçlü villages which were included in the consolidation program. In these villages, 62 farmers were selected by proportional sampling method out of 175 producers registered in the Farmer Registration System (FRS) and, face to face questionnaires were carried out with them. The results indicated that the producers support the project primarily due to the convenience in irrigation and increasing the efficiency of mechanization. Chi-square analysis revealed that the problems caused by disadvantages of fragmented land structure, importance of land integrity and the experience on a previous consolidation project area are important for the producers supporting the land consolidation project.


2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.


2012 ◽  
Vol 3 (4) ◽  
pp. 1-6 ◽  
Author(s):  
M.Jayalakshmi M.Jayalakshmi ◽  
◽  
P.Pandian P.Pandian

2019 ◽  
Vol 6 (04) ◽  
Author(s):  
ASHUTOSH UPADHYAYA

A study was undertaken in Bhagwanpur distributary of Vaishali Branch Canal in Gandak Canal Command Area, Bihar to optimally allocate land area under different crops (rice and maize in kharif, wheat, lentil, potato in rabi and green gram in summer) in such a manner that maximizes net return, maximizes crop production and minimizes labour requirement employing simplex linear programming method and Multi-Objective Fuzzy Linear Programming (MOFLP) method. Maximum net return, maximum agricultural production, and minimum labour required under defined constraints (including 10% affinity level of farmers to rice and wheat crops) as obtained employing Simplex method were ` 3.7 × 108, 5.06 × 107 Kg and 66,092 man-days, respectively, whereas Multi-Objective Fuzzy Linear Programming (MOFLP) method yielded compromised solution with net return, crop production and labour required as ` 2.4 × 108, 3.3 × 107Kg and 1,79,313 man-days, respectively. As the affinity level of farmers to rice and wheat crops increased from 10% to 40%, maximum net return and maximum production as obtained from simplex linear programming method and MOFLP followed a decreasing trend and minimum labour required followed an increasing trend. MOFLP may be considered as one of the best capable ways of providing a compromised solution, which can fulfill all the objectives at a time.


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