Crop production entails many decision making processes aimed at improving productivity and achieving the best yield from scarce resources, which are normally limited. Assuming that there is a certain technical path of tasks to be carried out within a period, and that each task can be done in different ways, the problem addressed in this paper consists of choosing how and when to carry out each one, in such a way that the tasks are scheduled in sequence at the lowest possible cost, taking account of any relations of precedence among them, and in such a way that each task is done within its time window and with the resources being assigned in a feasible way. Time windows are usually defined in a strict way, and thus, if adjusted, can be a cause of infeasibility for some of the problems, implying the need to acquire new resources. Nevertheless, in most cases small deviations from time windows could be acceptable. In this paper a mixed 0-1 programming model to attain the proposed objective is proposed, applying goal programming to model time windows in a more flexible way.
See Full PDF See Full PDFToday, in agricultural sectors, as in all other sectors too, the farmers are more concerned about the economical issues also. It is necessary for all the farmers to do their best to make as much effort as possible to increase the production and protect their crop. Due to changing weather conditions, water problems, labor problems and the economic conditions, agricultural sector management faces many constrains in order to achieve the required goal for production. It is obvious that one of the ways is to apply mathematical programming model for the agriculture sector. Economic planning is of vital importance in agriculture planning and applying fundamental programming methods is inevitable. The goal programming model for multi-objective programming is an important tool for studying various aspects of agriculture systems.
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This paper presents the results of reserach undertaken to assess the suitability of multiple criteria decision techniques to agricultural planning proble,s. The conventional mathematical programming paradigm as used in the form of linear programming is inadequate to deal with real agricultural planning problems when multiple goals and objectives are important elements of the situation. Goal programming and multiple objective programming techniques offer the most promising prospects of application to these problems; therefore, these programming structures are examined from that point of view, and the advantages over conventional approaches are examined.
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Agriculture is the main contribution to the rural economy of Sri Lanka. This study is carried on finding optimal land allocation for cultivation using goal programming approach. Five crops namely Cowpea, Black gram, Finger Millet, Maize and Soya Bean were selected to the study. This land allocation is for Anuradhapura District since it is the major agricultural district in Sri Lanka. Preemptive Goal Programming method is used in finding the optimal land allocation. Three goals are considered according to their priorities to seek the optimal solution. MS Excel Solver is used to implement the linear model. The data was collected from Annual Reports of Department of Agriculture. According to the final results obtained by goal programming approach, all five crops are reached their expected production. But the extent in yala (Dry Season) and maha (Rainy Season) season is changed. Overall result shows that new allocation exceeds the production and profit as well as minimizing the production cost. This mathematical model can easily be used on any other crop in any district by changing the variable coefficients and constraint values.
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2009 International Conference on Industrial and Information Systems (ICIIS)
This paper presents how the fuzzy goal programming (FGP) and interval valued goal programming (IVGP) can be efficiently used for modelling and solving land allocation problems for optimal production of seasonal crops in agricultural system. In the proposed approach, utilization of cultivable land, production of crops and target level of profit are fuzzily described. The supply and utilization of productive resources are considered interval valued to reach a satisfactory decision in the decision making environment. In the solution process, a genetic algorithm (GA) scheme is employed for achievement of the different goals on the basis of assigned weights of importance in the decision making situation. The potential use of the approach is demonstrated by a case example of the Nadia District, West Bengal (W. B.), INDIA.
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Brazilian Journal of Operations & Production Management
Goal: The present study aimed to demonstrate the applicability of the fuzzy goal programming to frame the decision support system for the decision-makers to deal with the real-life problem of the agriculture sector namely the apple cultivation planning problem and to obtain an optimum solution. Design / Methodology / Approach: The proposed method occurred within the apple-producing sector in the Kashmir valley of India and included the collection of data through interviews and surveys with various farmers. Also, the results were drawn with the help of LINGO 18.0. Results: The current finding implies that all of the desired objectives have been met, as well as an optimal solution. The proposed model offers a significant approach for designing plans to determine various agricultural activities in a fuzzy decision environment. Finally, the current study conducts a case study in the apple cultivation sector to obtain various competing objectives. Sensitivity analysis was also performed .
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Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie
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Predominance of agriculture is the third major problem of Indian economy. The economic contribution of agriculture to India's GDP is gradually on the way out with the country's broad-based economic growth. Lack of agricultural planning, monsoon failure, lack of water supply, lack of quality seeds, lack of fertilizers, lack of proper planning of apportionment of agricultural land and many more are the reasons for decrease of agricultural economic growth in India. This research work is an attempt to reveal the potential of goal programming for Agricultural land apportionment on a drought prone model district Ananthapur, Andhra Pradesh, India. It also intends the agricultural land apportionment for various major crops. The specific priorities used in the current goal programming problem are maximum utilization of agricultural land in the district, utilization of maximum available water sources, duration of the yield and needs of the district. This model of goal programming is solved by framing an objective function defined by the decision-maker and by converting the desired priority goals into linear constraints by introducing underachievement (di-) and overachievement (di+). The purpose of this research paper is to present the application of goal programming for the optimization of agricultural land apportionment and there by overcoming agrarian unsolved problems of drought prone districts of not only India, but also of the globe. This may even lead the drought prone districts to contribute directly or indirectly to the economy.
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Yugoslav Journal of Operations Research
This paper presents a fuzzy goal programming (FGP) approach for optimal allocation of land under cultivation and proposes an annual agricultural plan for different crops. In the model formulation, goals such as crop production, net profit, water and labor requirements, and machine utilization are modeled as fuzzy. A tolerance based FGP technique is used to quantify fuzziness of different goals for the problem. The fuzzy goals are transformed to linear constraints by introducing tolerance variables. The program then minimizes the values of the weighted sum of tolerance allowance variables for the highest membership grades, providing the most satisfactory set of allocations possible. As a measure of sensitivity, the problem is solved using different weight structures specified by the decision maker. A case study is provided to illustrate the usefulness of the method. .
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Journal of Agricultural Economics
