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.

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).

Optimization of groundwater resource for balanced cropping pattern

Water Policy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 643-657
Author(s):  
Smita Varade ◽  
Jayantilal N. Patel
Keyword(s):  
Water Resources ◽  
Optimization Model ◽  
Pso Algorithm ◽  
Cropping Pattern ◽  
Groundwater Levels ◽  
Net Returns ◽  
Tlbo Algorithm ◽  
Net Benefits ◽  
Optimal Cropping ◽  
Teaching Learning

Abstract In this paper, an optimization model is formulated and optimal cropping pattern is suggested. Conjunctive use of water is not feasible for the study area as groundwater is the only source to fulfil irrigation demand. Water resources for the study area are limited. Best utilization of available water resources for increased net benefits is always advisable. Sinnar Taluka of Nasik district of Maharashtra state in India is considered as a study area. An existing cropping pattern is studied extensively and a new cropping pattern is suggested. Teaching–learning-based algorithm (TLBO) and particle swarm optimization (PSO) algorithm are applied to solve the optimization model. TLBO algorithm provides higher net returns as compared to PSO algorithm. TLBO and PSO saves up to 16.52% of water and benefits are increased by 35.81%. The study area is overexploited, this is fact. The new cropping pattern is suggested by considering minimum rainfall, i.e., 400 mm, so that in years when rainfall is above minimum rainfall the groundwater levels will be raised. In the proposed cropping pattern a few crop areas are majorly increased and a few crop areas are majorly reduced. The remaining crop areas are minorly increased or reduced and net benefits are increased and water demand decreased.

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 Optimal Land And Water Allocation Model For The Maximization of Net Agricultural Return In Drought Prone Regions

2021 ◽  
Author(s):  
Mulu Sewinet Kerebih ◽  
Ashok Kumar Keshari
Keyword(s):  
Water Resources ◽  
Rainfall Variability ◽  
Resources Allocation ◽  
Command Area ◽  
Cropping Pattern ◽  
Water Resources Allocation ◽  
Allocation Model ◽  
Cropping Patterns ◽  
The Government ◽  
Optimal Cropping

Abstract In this study, the land and water resources allocation model was developed to determine optimal cropping patterns and water resources allocations at different rainfall probability exceedance levels (PEs) to ensure maximum agricultural return in the Hormat-Golina valley irrigation command area, Ethiopia. To account the uncertainty of rainfall variability, the monthly dependable rainfall was estimated at three levels of reliability (20, 50 and 80% PEs) which are representing wet, normal and dry seasons based on regional experience. The irrigation water demand which was used as an input to the optimization model was estimated at each level of reliability by using CROPWAT model. The net annual returns of optimal cropping patterns were estimated as 181, 179 and 175 million Ethiopia Birr at 20 %, 50 % and 80 % PEs, respectively. The result of the optimal cropping pattern indicates that, the net annual return of the command area was increased to 45.75%, 45.84% and 47.01% than the Government targeted at 20%, 50% and 80% PEs, respectively. The findings reveal that the optimal land and water resources allocation model is very useful to the planners and decision makers to maximize the agricultural return particularly in areas where land and water resources are limited.

scholarly journals Multi-objective reservoir operation of the Ukai reservoir system using improved Jaya algorithm

2021 ◽  
Author(s):  
Vijendra Kumar ◽  
S. M. Yadav
Keyword(s):  
Particle Swarm Optimization ◽  
Reservoir Operation ◽  
Particle Swarm ◽  
Jaya Algorithm ◽  
Hydropower Generation ◽  
Invasive Weed ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Better Than ◽  
Self Adaptive

Abstract This paper introduces an effective and reliable approach based on multi population approach, namely self-adaptive multi-population Jaya algorithm (SAMP-JA), to extract multi-purpose reservoir operation policies. The current research focused on two goals: minimizing irrigation deficits and maximizing hydropower generation. Three different models were formulated. The results are compared with ordinary Jaya algorithm (JA), particle swarm optimization (PSO), and Invasive weed optimization (IWO) algorithm. In Model-1, the minimum irrigation deficit was obtained by SAMP-JA and JA as 305092.99 . SAMP-JA was better than JA, PSO and IWO in terms of convergence. In Model-2, the maximum hydropower generation was achieved by SAMP-JA, JA and PSO as 1723.50 . While comparing the average hydropower generation SAMP-JA and PSO performed better than JA and IWO. In terms of convergence, SAMP-JA was better than PSO. In Model-3, self-adaptive multi-population multi objective Jaya algorithm (SAMP-MOJA) was better than multi objective particle swarm optimization (MOPSO) and multi objective Jaya algorithm (MOJA) in terms of maximum hydropower generation, and MOPSO was better than SAMP-MOJA and MOJA in terms of minimum irrigation deficiency. While comparing convergence, SAMP-MOJA was found to be better than MOPSO and MOJA. Overall, SAMP-JA was found to be outperforming than JA, POS and IWO.

scholarly journals "Quantification of Incremental Benefits and Change in Input Use Pattern under Laser Land Levelling in comparison with Conventional Land Levelling in Haryana"

2021 ◽  
Vol 66 (2) ◽  
Author(s):  
Dinesh , Kumar
Keyword(s):  
Plant Protection ◽  
Resource Conservation ◽  
Cropping Pattern ◽  
Cropping Patterns ◽  
Input Use ◽  
Land Leveling ◽  
Human Labor ◽  
Conservation Technology ◽  
Net Benefits ◽  
Use Pattern

The investigation aimed to find monetary benefits of Laser Land Levelling (LLL) compared to conventional land leveling (CLL) in Karnal and Sirsa district of Haryana. These two districts were selected purposively because these have the highest area under paddy-wheat and cotton-wheat cropping patterns, respectively. The equation of Aryal et al. (2014) was explicitly used to estimate incremental benefits from laser land leveling. Also, input use pattern of machine labor, seed, plant protection chemicals, human labor, yield, and irrigation was considered. In the paddy-wheat cropping pattern of Karnal district, the annual net benefits of using laser land levelling were estimated to be ` 11450.81. In contrast, per LLL operation, net benefits were estimated to be ` 34352. Similarly, on the same lines in the cotton-wheat cropping pattern of Sirsa district, the annual net benefits of LLL were estimated to be ` 7212.61. In contrast,per LLL operation, net benefits were estimated to be ` 28850. As far as the input use pattern is concerned, the study showed that machine labour and yield increased under LLL while in both districts. In contrast, all other inputs i.e., seed, fertilizer, human labor, plant protection, chemicals, irrigation, were reduced, showing resource conservation potential of LLL. Hence, the study recommended adopting this resource conservation technology and tapping its potential benefits so that farmers may get benefitted from this ultimate technology

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.  

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.

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