scholarly journals Multi Crop Optimization Using Linear Programming Model for Maximum Net Benefit

2018 ◽  
Vol 7 (3.12) ◽  
pp. 797
Author(s):  
Shreedhar R
Keyword(s):  
Linear Programming ◽  
Water Resources ◽  
Water Availability ◽  
Programming Model ◽  
Optimization Techniques ◽  
Cropping Pattern ◽  
Economic Returns ◽  
Net Benefit ◽  
Use Of Resources ◽  
Optimal Cropping

The water used for agriculture is 70% globally. This has resulted in new methods of saving water. Hence water saving techniques has to be practiced.  In water resources planning and management, optimization techniques is used for limited use of resources such as such as water, land, production cost, manpower, fertilizers, seeds, and pesticides. For cultivating each crop, the land area needs to be planned properly. Hence the crop pattern has to be decided optimally depending on available water resources and on economic basis. Therefore farmer needs to be educated to adopt optimum cropping pattern which maximises the economic returns. Hence the study is taken up to optimize the allocation of land areas to crops. The objective function for multi crop model were formulated using linear programming for maximizing the net benefits. The study resulted in optimal cropping pattern for different water availabilities ranging from 2000 Ha-m to 5500 Ha-m. The maximum net benefit for the study area varied from Rs. 53.2 Crores for 2000 Ha-m water availability to Rs.78 Crores at 5000 Ha-m water availability.  

Optimal crop planning using a chance constrained linear programming model

Water Policy ◽  
2011 ◽  
Vol 13 (5) ◽  
pp. 734-749 ◽  
Author(s):  
V. Jothiprakash ◽  
R. Arunkumar ◽  
A. Ashok Rajan
Keyword(s):  
Linear Programming ◽  
Probability Distribution ◽  
Programming Model ◽  
Linear Programming Model ◽  
Cropping Pattern ◽  
Net Benefit ◽  
Cropping Patterns ◽  
Time Period ◽  
Irrigation Intensity ◽  
Optimal Cropping

A monthly time-stepped chance constrained linear programming (CCLP) model was developed to derive optimal cropping patterns and optimal operational strategies for the Sri Ram Sagar Project, with stochastic inflows. The stochastic nature of the inflows was incorporated into the model in its equivalent deterministic form. These equivalent deterministic inflow values were estimated from the annual and monthly probability distribution of observed inflows, and named the chance constrained linear programming model-annual and chance constrained linear programming model-monthly, respectively. The models were solved for nine different dependable inflow levels, namely for 50, 55, 60, 65, 70, 75, 80, 85 and 90% in each CCLP. The results of the models were compared with respect to net benefit, irrigation intensity, total cropped area, optimal cropping pattern, optimal releases, evaporation loss and initial storages. Based on the results obtained, it can be concluded that, in CCLP optimization, the probability distribution of ‘model time period’ (t-month in this case) should be considered rather than the probability of ‘planning time period’ (year in this case).

scholarly journals PLANO ÓTIMO DE CULTIVO NO PROJETO DE IRRIGAÇÃO MORADA NOVA, CEARÁ, UTILIZANDO MODELO DE PROGRAMAÇÃO LINEAR

Irriga ◽  
2000 ◽  
Vol 5 (3) ◽  
pp. 167-187
Author(s):  
José Aurélio Lucena Rodrigues ◽  
Raimundo Nonato Távora Costa ◽  
José Antônio Frizzone ◽  
José Vanglésio de Aguiar
Keyword(s):  
Linear Programming ◽  
Water Supply ◽  
Programming Model ◽  
Linear Programming Model ◽  
Water Volume ◽  
Land Resource ◽  
Cropping Pattern ◽  
Irrigation Project ◽  
Optimal Cropping Pattern ◽  
Optimal Cropping

PLANO ÓTIMO DE CULTIVO NO PROJETO DE IRRIGAÇÃO  MORADA NOVA, CEARÁ, UTILIZANDO MODELO DE PROGRAMAÇÃO LINEAR  José Aurélio Lucena RodriguesDepartamento Nacional de Obras Contra as Secas – Av. Duque de Caxias.CEP 60000-000 – Fortaleza-CERaimundo Nonato Távora CostaUniversidade Federal do Ceará – Departamento de Engenharia Agrícola. Campus do Pici. Bloco 804.CEP 60455-760 – Fortaleza-CEJosé Antônio FrizzoneEscola Superior de Agricultura Luiz de Queiroz – Departamento de Engenharia Rural,  Av. Pádua Dias, 11 – Caixa Postal 11. 13418-900 – Piracicaba-SPJosé Vanglésio de AguiarUniversidade Federal do Ceará – Departamento de Engenharia Agrícola. Campus do Pici. Bloco 804.CEP 60455-760 – Fortaleza-CE  1 RESUMO O objetivo do trabalho foi desenvolver um modelo de programação linear para quantificar as variáveis do processo de produção, que otimizem a operação do Projeto de Irrigação Morada Nova (PIMN). O modelo procura estabelecer um plano ótimo de cultivo, objetivando a maximização da sua receita líquida anual. Na análise do modelo foram incorporadas as restrições de volume de água mensal, volume de água anual, terra, mercado. Com base nas culturas estudadas,  nas restrições de área cultivada, nos preços e nos custos de produção, os resultados permitiram as seguintes conclusões: 1) o modelo de programação linear recomendou os cultivos de 1050 ha de arroz semeado em fevereiro, 1050 ha de arroz semeado em agosto, 750 ha de feijão semeado em julho, 130 ha de milho (espiga) semeado em janeiro, 155 ha de banana e 112 ha de coco para um volume de água utilizado de 30.285.5460 m3;  2) modelo de otimização desenvolvido projetou uma receita líquida 19,06 % maior que a obtida com o  plano de cultivo do PIMN e um volume anual utilizado inferior em 47,3 %, considerando o ano agrícola de 1997; 3) a ocupação da terra foi baixa, com percentuais médios anuais de 41,4% e 40,3% respectivamente, para o modelo proposto e o plano de cultivo do PIMN; 4) a análise de sensibilidade do recurso terra apresentou preço sombra zero, indicando que esse recurso não foi restritivo; 5) mantendo-se o volume mensal disponível em 7.516.400 m3 e  9.730.700 m3 respectivamente, para os períodos de janeiro a junho e julho a dezembro, volumes anuais superiores a 30.285.560 m3 não contribuíram para o  aumento da  receita líquida do PIMN. UNITERMOS: Programação linear, padrão de cultivo, irrigação.  RODRIGUES, J. A .L., COSTA, R. N. T., FRIZZONE, J. A., AGUIAR, J. V. OPTIMAL CROPPING PATTERN IN THE “MORADA NOVA” IRRIGATION PROJECT USING LINEAR PROGRAMMING MODEL 2 ABSTRACT The main objective of this work was to develop a linear programming model, in order to quantify the process variables which optimize the irrigation project operation. The model establishes optimal cropping pattern in the irrigation project “Morada Nova” (MNIP), aiming to maximize the net annual income. Restrictions to the model were monthly water supply, anual water supply, land and market system. Based on the water-yield considered, cultivated land restrictions, production cost and product prices, the following conclusions were reached: 1) the model rresulted a optimal cropping pattern comprising 1050 ha  of  rice cultivated in February, 1050 ha of rice cultivated in August, 750  ha of beans (vigna) cultivated in July, 130 ha of corn (cob) cultivated in January, 155 ha of banana and 112 ha of cocunut, for a total annual utilized water of 30.285.560 m3; 2) the optimization model presented, estimated a net income of 19,06 % higher than  cropping pattern used in the MNIP, using an  annual water volume 47,3 % lower,  considering the agricultural year of 1997; 3)  the land occupation was low with annual average percentages of 41,4% e 40,3% respectively, to the presented model and the cropping pattern used in the MNIP; 4)  the sensibility analysis to the land resource revealed dual price zero, indicating that this recource was not restrictive; 5) maintaining the total monthly availability of 7.516.400 m3 and 9.730.700 m3 respectively, in the periods from January until June and from July  until December respectively, annual volumes higher than 30.285.560 m3, did not increase the  return of the MNIP. KEYWORDS: Linear programming, cropping pattern, irrigation.

scholarly journals Use of Linear Programming Model to Determine the Optimum Cropping Pattern for an Irrigation Scheme in Masvingo, Zimbabwe

2013 ◽  
Vol 1 (4) ◽  
pp. 450-452
Author(s):  
Majeke F ◽  
Mubvuma S M T ◽  
J. Chirima, K. Makaza ◽  
T. Hungwe R. Gwazan ◽  
Nyoni ◽  
...  
Keyword(s):  
Linear Programming ◽  
Optimization Problems ◽  
Programming Model ◽  
Optimal Solution ◽  
Linear Programming Model ◽  
No Production ◽  
Cropping Pattern ◽  
Irrigation Scheme ◽  
Irrigation Planning ◽  
Optimal Cropping

Agricultural systems are often faced by challenges such as crop selection and irrigation planning which can be formulated as optimization problems. Decisions have to be made on the proper set of crops to be cultivated and a proper irrigation scheme. The objectives of such decisions are to maximize net profit or to minimize water waste. In this study, a linear programming model was developed that helped to determine the optimal cropping pattern for an irrigation scheme in Masvingo, Zimbabwe. Crops which considered were wheat, sugar beans for winter and cotton and maize for summer for the 2012/13 agricultural season. The linear programming model was solved by using Microsoft Excel (2007). The model recommended no production of wheat and cotton. Sugar beans and maize gained acreage by 50 percent and 88 percent respectively. On the whole, the optimal cropped acreage did not change as compared to the existing cropping plan. As a result of the optimal solution, a farmer‘s income could be increased by $1,668.60. The optimal income increased from existing level of $1,919.40 to $3,588.00 showing an improvement of 87 percent. The results show that LP models solutions are worthy implementing.

scholarly journals Hybrid Optimization Model for Conjunctive Use of Surface and Groundwater Resources in Water Deficit Irrigation System

2021 ◽  
Author(s):  
Karthikeyan MoothampalayamSampathkumar ◽  
Saravanan Ramasamy ◽  
Balamurugan Ramasubbu ◽  
Hamid Reza Pourghasemi ◽  
Saravanan Karuppanan ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Deficit ◽  
Optimization Model ◽  
Conjunctive Use ◽  
Hybrid Optimization ◽  
Cropping Pattern ◽  
Net Benefit ◽  
Hybrid Optimization Model ◽  
Optimal Cropping ◽  
Surface And Groundwater

Increasing demand for food production with limited available water resources pose the threat to agricultural activities. The conjunctive allocation of water resources maximizes the net benefit of farmers efficiently. In this study, a novel hybrid optimization model was developed based on a genetic algorithm (GA), bacterial foraging optimization (BFO) and ant colony optimization (ACO) to maximize the net benefit of water deficit Sathanur reservoir command. The GA-based opti-mization model considered crop-related physical and economical parameters to derive optimal cropping patterns for three different conjunctive use policies and further allocation of surface and groundwater for different crops are enhanced with the BFO. The allocation of surface and groundwater for the head, middle and tail reach obtained from BFO is considered as input to ACO as a guiding mechanism to attain an optimal cropping pattern. Comparing the average produc-tivity values Policy 3 (3.665 Rs/m3) has better values relating to Policy 1 (3.662 Rs/m3) and Policy 2 (3.440 Rs/m3). Thus, the developed novel hybrid optimization model (GA-BFO-ACO) is very promising to enhance the farmer's net income as well as for the command area water conservation and can be replicated in other irrigated regions of the globe to overcome chronic land and water problems.

Linear Programming Model for the Design of Optimal Cropping Pattern for a Major Distributary Canal

2021 ◽  
pp. 57-67
Author(s):  
S. B. Ganesh Kumar ◽  
B. R. Ramesh ◽  
H. J. Surendra
Keyword(s):  
Linear Programming ◽  
Programming Model ◽  
Linear Programming Model ◽  
Cropping Pattern ◽  
Optimal Cropping Pattern ◽  
Optimal Cropping

scholarly journals Hybrid optimization model for conjunctive use of surface and groundwater resources in water deficit irrigation system

2021 ◽  
Author(s):  
Karthikeyan Moothampalayam Sampathkumar ◽  
Saravanan Ramasamy ◽  
Balamurugan Ramasubbu ◽  
Saravanan Karuppanan ◽  
Balaji Lakshminarayanan
Keyword(s):  
Water Resources ◽  
Water Deficit ◽  
Optimization Model ◽  
Conjunctive Use ◽  
Hybrid Optimization ◽  
Cropping Pattern ◽  
Net Benefit ◽  
Hybrid Optimization Model ◽  
Optimal Cropping ◽  
Surface And Groundwater

Abstract The Increasing demand for food production with limited available water resources poses a threat to agricultural activities. Conventional optimization algorithm increases the processing stage and it performed with in the space, which is allocated from user. Therefore, the proposed work is utilized to design with better performance results. The conjunctive allocation of water resources maximizes the net benefit of farmers. In this study, a novel hybrid optimization model developed is first of its kind to resolve the sharing of water resources conflict among different reaches based on a genetic algorithm (GA), bacterial foraging optimization (BFO) and ant colony optimization (ACO) to maximize the net benefit of the water deficit Sathanur reservoir command. The GA-based optimization model considered crop-related physical and economic parameters to derive optimal cropping patterns for three different conjunctive use policies and further allocation of surface and groundwater for different crops are enhanced with the BFO. The allocation of surface and groundwater for the head, middle and tail reaches obtained from BFO is considered as an input to the ACO as a guiding mechanism to attain an optimal cropping pattern. Comparing the average productivity values, Policy 3 (3.665 Rs/m3) has better values relating to Policy 1 (3.662 Rs/m3) and Policy 2 (3.440 Rs/m3). Thus, developed novel hybrid optimization model (GA-BFO-ACO) is very promising for enhancing farmer's net income and can be replicated in other irrigated regions to overcome chronic water problems. The productivity value of policy 3 was 6.54% greater than that of policy 2, whereas that of policy 1 was 6.45% greater. Overall, the comparison shows the better performance analysis of various optimization is done successfully.

Impact of Optimal Cropping Patterns on Incomes in a Punjab District

1976 ◽  
Vol 15 (2) ◽  
pp. 218-221
Author(s):  
M. Arshad Chaudhry
Keyword(s):  
Developing Countries ◽  
Linear Programming ◽  
Short Note ◽  
Cropping Pattern ◽  
Small Farms ◽  
Cropping Patterns ◽  
Punjab Province ◽  
Optimal Cropping

To improve farm incomes in developing countries, the foremost question that the farmer must address himself to is: what cropping pattern best uses the fixed resources in order to get the highest returns? During the last decade, the agricultural economists have shown great interest in applying the tools of linear programming to individual farms. Most of the studies conducted elsewhere have shown that, under existing cropping pattern, farm resources were not being utilized optimally on the small farms.[l, 4]. We conducted a survey in the canal-irrigated areas of the Punjab province of Pakistan1 to investigate into the same problem. This short note aims at identifying the opti¬mal cropping pattern and to estimate the increase in farm incomes as a result of a switch towards it on the sampled farms.

scholarly journals Research of the College Enrollment Plan Based on Fuzzy Linear Programming Model

2021 ◽  
Vol 251 ◽  
pp. 01092
Author(s):  
Yuhong Sun ◽  
Guoxing Zhang ◽  
Yueyang Gao ◽  
Mingzhu Chen
Keyword(s):  
Linear Programming ◽  
Mathematical Models ◽  
Hierarchical Structure ◽  
College Enrollment ◽  
Programming Model ◽  
College Admission ◽  
Fuzzy Linear Programming ◽  
Linear Programming Model ◽  
Use Of Resources ◽  
Linear Programming Methods

This paper aims at the problems of professional structure and hierarchical structure in college admission plans, uses linear programming methods to establish mathematical models, maximizes the use of resources on the basis of completing the national enrollment plan, determines the reasonable enrollment structure and enrollment scale, and makes the enrollment plan more scientific and reasonable. In actual situations, the number of students enrolled in the school, the consumption of students, and the number of teachers are constantly changing. Therefore, the concept of fuzzy linear programming is introduced, and the constraints of the linear programming model are fuzzy optimized to obtain more reasonable results, which inspires some reasonable suggestions for colleges in formulating enrollment plans.

scholarly journals Self-adaptive multi-population-based Jaya algorithm to optimize the cropping pattern under a constraint environment

2019 ◽  
Vol 22 (2) ◽  
pp. 368-384
Author(s):  
Vijendra Kumar ◽  
S. M. Yadav
Keyword(s):  
Population Based ◽  
Cropping Pattern ◽  
Jaya Algorithm ◽  
Net Benefit ◽  
Invasive Weed ◽  
Cropping Patterns ◽  
Net Benefits ◽  
Optimal Cropping ◽  
Teaching Learning ◽  
Self Adaptive

Abstract Increasing population around the world, especially in India and China, has resulted in a drastic increase in water intake in both domestic and agricultural sectors. This, therefore, requires that water resources be planned and controlled wisely and effectively. With this consideration, the aim of the study is to achieve an optimal cropping pattern under a constrained environment. The objective is to maximize the net benefits with an optimum use of water. For optimization, a self-adaptive multi-population Jaya algorithm (SAMP-JA) has been used. For the Karjan reservoir in Gujarat State, India, two different models, i.e. maximum and average cropping patterns, were formulated based on the 75 per cent dependable inflow criteria. These two model scenarios are developed in such a way that either model can be selected by the farmer based on the crop area and its respective net benefits. Invasive weed optimization (IWO), particle swarm optimization (PSO), differential evolution (DE) and the firefly algorithm (FA) were compared to the results. The results show that the SAMP-JA obtained the maximum net benefit for both the models. The findings of the research are also compared with the actual cropping pattern. A significant increase has been noted in the cultivation of sugarcane, groundnut, wheat, millet, banana and castor. SAMP-JA has been noted to converge faster and outperforms PSO, DE, IWO, FA, teaching–learning-based optimization (TLBO), the Jaya algorithm (JA), elitist-JA and elitist-TLBO.

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