Browsing by Author "Hakmanage, N.M."

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Application of fuzzy goal programming model to assess optimal multi crop cultivation planning
(Agriculture and Natural Resources, 2022) Hakmanage, N.M.; Chandrasekara, N.V.; Jayasundara, M.
Importance of the work: Planning for the optimal use of resources in agricultural systems considering uncertainty, with the objective of maximizing profit and production, will improve the social and economic conditions of farmers. Objectives: A rural farming area in Sri Lanka was used as a study site to apply the fuzzy goal programming (FGP) approach to identify the optimal cultivation plan and land resource allocation under uncertainty to optimize profit, production, labor, water use, fertilizer costs and land allocation. Materials & Methods: A tolerance-based FGP technique was used to quantify the fuzziness of different goals for the model. This study was carried out using 24 crops on a total land area under cultivation of 47.4 ha. These crops were categorized into three varieties: vegetable, fruit and other. Furthermore, the crops were classified into seven groups according to the required period of cultivation. Results: The proposed model suggested statistically significant increments of 11% and 10.6% for the net return and harvest amount, respectively, for the 24 crops compared to existing cultivation techniques.Main finding: The FGP multi-crop cultivation planning approach is a new application for the Sri Lankan rural farming community and it should be useful for agricultural planners, by allowing them to make more informed recommendations to the farming community. Crops that provide higher levels of production and profit than those currently being cultivated should be developed to extend cultivation under the supervision of agricultural experts or officers to obtain sustainable development of cultivation.
Linear programming approach to assess an optimal cultivation plan: A case study
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Hakmanage, N.M.; Chandrasekara, N.V.; Jayasundara, D.D.M.
An optimal cultivation plan refers to the procedure or action of making the best or most effective use of resources for cultivation in a sustainable manner while maximizing net return. Reaching an efficient cultivation plan and utilization of resources and requirements is often a challenging problem. To utilize resources and requirements such as water, land, manpower, fertilizers and seeds, optimization techniques are used. The objective of this research is to maximize the net return of the cultivation using linear programming technique and allocate the arable land optimally. Linear programming is the most convenient and effective tool to handle the objective function with many constraints. This study was carried out in a rural village located in Dompe divisional secretariat in Gampaha district using 150 farming lands, to determine the land resource allocation for twelve selected crops: bitter gourd, lady's fingers, manioc, potatoes, rambutan, banana, pineapple, beetle, rice, coconut, tea and pepper. The linear programming model is formulated for the optimal land resource allocation of 4477.2 perches. The maximum net return projected by the proposed model is Rs 6,370,512.00 for cultivation seasons. The proposed solution is a 34.96% increase in profit as compared to the actual profit obtained from the cultivations. Crops like rambutan, rice, manioc and pineapple which provides a higher return should be developed and cultivation extended under the supervision of the agricultural expertise or officers. The model suggests that some crops such as lady’s fingers, potatoes, banana and coconut may not be providing comparable returns versus the other selected crops. The results reveal that linear programming approach will significantly improve the net benefits with optimal crop area allocation. The limitation of this study is that it is considered the soil condition is the same for all crops in the study area. Advanced operations research techniques like multi objective nonlinear programming models will be employed for this study in future work.
Modeling and Forecasting Selected Climatic Factors Influenced on Sustainable Cultivation Plan: A Case Study for Dompe-Gampaha District
(International Postgraduate Research Conference 2019, Faculty of Graduate Studies, University of Kelaniya, Sri Lanka, 2019) Hakmanage, N.M.; Chandrasekara, N.V.; Jayasundara, D.D.M.
The agriculture is the back born of economy of the most Asian countries. Although the country is moving towards industrialization, the agricultural sector still continues to be an important sector in the economy in Sri Lanka. Cultivation is the predominant sector of the agriculture. Lack of sufficient amount of water is the main limitation factor for cultivation while flood/ deluge is causing the waste of harvest. The main water source for cultivation in Sri Lanka is rainfall. Moreover, for each crop due to its peculiarities and mainly owing to its geographical origin, there exist specific temperature limits within which these plants are able to grow and reproduce. Hence rainfall and temperature are imperative factors influenced on cultivation. More accurate forecasting of monthly rainfall and temperature is significantly important in irrigation schedule, water resources management, crop pattern design and designing of harvesting amount. The main objective of this study is to build suitable forecasting models for two climatic factors: Temperature and Rainfall which affect sustainable cultivation plan. Monthly data of rainfall and temperature from 2009 to 2019 of Dompe-Gampaha district was considered for the study. First 80% of data was used to formulate the models and the rest 20% data was used to validate the models. The paper introduces two fundamentally different approaches for designing a model, the statistical method based on seasonal autoregressive integrated moving average (SARIMA) and decomposed ARIMA model. Mean absolute percentage error (MAPE), Root mean squared error (RMSE) was used to evaluate the performance of fitted models. Among the fitted ten models, SARIMA(0,0,0)(1,0,1)12 was identified as the better model to forecast rainfall based on minimum Akaike information criterion (AIC) where MAPE and RMSE are 48.57% and 5.1339 respectively. Although Box Ljung lack of fit test prove that this model is suitable model, the errors are extremely high. Then decompose ARIMA model was used by calculating seasonal and trend component using SARIMA(0,0,0)(0,1,0)12 and linear regression (Trend=14.33321–0.04884*time) models respectively. Summation of forecasted values of these two models is the forecasted value of decompose ARIMA model and it exhibits MAPE which is 20% lower than the SARIMA(0,0,0)(1,0,1)12 model. Therefore, fitted decomposed ARIMA model can be recommend as a better model to forecast rainfall of Dompe-Gampaha district. Similar approach was carried out to find a suitable model to forecast temperature. SARIMA(1,0,0)(2,0,1)12 was the most accurate model to forecast temperature with minimum AIC value. MAPE and RMSE of this model was 1.3938% and 0.4695 respectively. Lack of fit test and errors provide evidence to say that the fitted SARIMA(1,0,0)(2,0,1)12 is suitable to forecast temperature in the study area. The forecasted values of rainfall and temperature can be used when developing sustainable cultivation plan in Dompe-Gampaha district which leads to development of agricultural sector of the country
Optimal assignment of unusable/ waste lands effectively using improved fuzzy assignment technique
(Faculty of Graduate Studies - University of Kelaniya, Sri Lanka, 2021) Hakmanage, N.M.; Jayasundara, D.D.M.; Chandrasekara, N.V.
Land resources are valuable for humans not only live but also conduct all of their economic activities on it. Allocation of land uses in a critical and optimal manner will pave the way for determining policies for the optimal utilization of land in a sustainable manner for the future, focusing on the uncertain conditions of each allocation. The objective of this study is to identify and propose effective allocations to abandoned lands such as unusable, waste and uncultivable lands using optimal land assignment plan. Fuzzy assignment technique accesses to explore how uncertainty in suitability index and the condition of the land will affect to optimal land allocation with the minimum allocation cost in this study. A major land-use classification system in Sri Lanka contains multiple levels of classification. Among them, land use categories regarded to the study area (farming village which has six unusable lands in Dompe divisional secretariat, Gampaha District) are selected as follows: Agriculture, Habitable or settled lands (Urban or rural areas), Forests, Wildlife, Reserves & Catchments areas, Underutilized Lands, Reservations (Reservoirs, Streams, & Irrigation Channels) and Barren lands. Major properties of the land were identified as land area: vaguely defined categories measured in square meters; Ownership: three possible sectors according to the ownership of the land as Private, Public and Other; Condition: discretional parameter that is vaguely defined with three possible values: bad (0), average (0.5) and good (1) and the Facilities: four different categories (power (P), water (W), communication (C), transportation (T)). Subsequently, the properties of each land and all possible demands were identified and a suitability index was developed using those vague parameters for each assignment of lands. With the aid of the Center of Gravity (COG) method, fuzzy values were converted to their crisp equivalents. Then the cost of assignment of each land for the aforementioned purposes, were considered using with linear, triangular, and trapezoidal fuzzy membership intervals. Thereafter, Robust ranking technique was applied to calculate the numerical values for the interval and obtain the product of suitability index and cost of allocation. Finally, using the Hungarian assignment algorithm, each land was assigned optimally for its effective purposes. The linear, triangular, and trapezoidal membership degrees, the minimum cost was obtained from the trapezoidal membership degree, that is 15% lower than the linear membership degree. Therefore, study proceeds with the trapezoidal membership degree. Using hypothetical assignment costs, six lands in the study area were assigned optimally for agriculture, habitable or settled lands, forests, wildlife, reserves and catchments areas, underutilized lands, reservations, and barren lands. This will be a great social and environmental service as it will involve the re-usage of the lands that are currently abandoned. Furthermore, the findings of this study can be extended nationally to save and maintain the land resource in an optimal manner.
Statistical and Mathematical Models for a Sustainable Cultivation Plan - A Brief Review of the Literature
(International Conference on Applied Social Statistics (ICASS) - 2019, Department of Social Statistics, Faculty of Social Sciences, University of Kelaniya, Sri Lanka, 2019) Hakmanage, N.M.; Chandrasekara, N.V.; Jayasundara, D.D.M.
Due to rapid increase of population, demand for food is increasing. If the agricultural sector fails to supply and meet the rising demand of foods, it will affect the economy. This however requires finding viable solution that is balanced supply demand food chain. To fulfil subsistence food needs there should be a stationary state with proper cultivation plans in agricultural sector in a country. This study presents a review of the literature published between 1998 and 2019 on cultivation plans in the areas of statistics and/ or mathematics which have considered major influential factors for cultivation. This study aims at reviewing the most appropriate sub sections: arable land selection, cultivating methodologies and climatic factors effect on cultivation to build an optimal cultivation plan. Review was conducted using separate articles as searching strategy was failed to identify published articles which studied for these three aspects together. Hence the significance of this study is to discuss how to apply statistical and/ or mathematical models which are used to implement the cultivation plan including all influential factors together