IMPROVEMENT OF AGRICULTURAL MACHINERY ASSIGNMENT MODEL BY COMPUTER SIMULATION

Agricultural producers who possess large areas of arable land and a lot of machinery can achieve substantial savings, thus improving their business performance, if they manage to ensure adequate assignment of machinery to appropriate jobs during the entire production cycle. When attempting to establ...

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Bibliographic Details
Published inCereal research communications Vol. 36; pp. 139 - 142
Main Authors DUKIĆ, Darko, DUKIĆ, Gordana, SESAR, Mate
Format Journal Article
LanguageEnglish
Published Akadémiai Kiadó 01.01.2008
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Summary:Agricultural producers who possess large areas of arable land and a lot of machinery can achieve substantial savings, thus improving their business performance, if they manage to ensure adequate assignment of machinery to appropriate jobs during the entire production cycle. When attempting to establish the optimum assignment set of agricultural machinery, a variety of factors need to be taken into consideration, for example the features of human and technical resources engaged in production, weather conditions, characteristics of soil and crops, distance of fields from the machinery storage space. In this domain it is possible to use the assignment model as a decision support. The initial assignment model, which is deterministic in character, has undergone improvements in this paper by means of computer simulation, which makes it suitable for usage in conditions of uncertainty, which are quite common in agriculture. In the proposed model, simulation is carried out for the values of all the parameters estimated to be stochastic. On the basis of scores assigned according to set criteria, the efficiency matrix is then formed, whose elements represent the expected benefits from assigning the machinery to particular activities in agriculture. The optimum assignment set of agricultural machinery is the one in which the sum of efficiency for all assignments is maximum. Usage of modern information technologies is an essential prerequisite for implementing the model discussed in this paper.
ISSN:0133-3720
1788-9170
DOI:10.1556/CRC.36.2008