Joanna Makulska | University of Agriculture in Krakow (original) (raw)
Papers by Joanna Makulska
ABSTRACT Herd management requires taking many breeding and production decisions. Most beneficial ... more ABSTRACT Herd management requires taking many breeding and production decisions. Most beneficial decisions, taken based on accepted criteria, can be facilitated using mathematical programming and modeling methods. The model is a simplified representation of a system (farm, company, production process) used to detect quantitative relations between variables in the analysed system and to predict the effect of changes in the values of these variables. Models are solved and optimum decisions made using mathematical programming techniques. A special role among these techniques is played by dynamic programming extended with Hierarchic Markov Processes (HMP). This method is used to support economically optimal decisions concerning rearing and introduction of replacement heifers to dairy herds, data of insemination and rotation of dairy herd, as well as the course of individual and group bull fattening. The development of Multi-Level Hierarchic Markov Processes (MLHMP), in which the hierarchic structure of the model was extended with new levels, made it possible to solve more complex decision problems. The examples of using this method to support cattle herd management decisions include a model for optimization of fattening length and slaughter weight of bullocks, and efforts aimed at constructing a model for optimization of breeding heifer use strategy in a beef herd.
Annals of Warsaw Agricultural University. Animal Science, 2000
Asian-Australasian Journal of Animal Sciences, 2017
Ahead of Print article withdrawn by publisher.
ABSTRACT Herd management requires taking many breeding and production decisions. Most beneficial ... more ABSTRACT Herd management requires taking many breeding and production decisions. Most beneficial decisions, taken based on accepted criteria, can be facilitated using mathematical programming and modeling methods. The model is a simplified representation of a system (farm, company, production process) used to detect quantitative relations between variables in the analysed system and to predict the effect of changes in the values of these variables. Models are solved and optimum decisions made using mathematical programming techniques. A special role among these techniques is played by dynamic programming extended with Hierarchic Markov Processes (HMP). This method is used to support economically optimal decisions concerning rearing and introduction of replacement heifers to dairy herds, data of insemination and rotation of dairy herd, as well as the course of individual and group bull fattening. The development of Multi-Level Hierarchic Markov Processes (MLHMP), in which the hierarchic structure of the model was extended with new levels, made it possible to solve more complex decision problems. The examples of using this method to support cattle herd management decisions include a model for optimization of fattening length and slaughter weight of bullocks, and efforts aimed at constructing a model for optimization of breeding heifer use strategy in a beef herd.
Annals of Warsaw Agricultural University. Animal Science, 2000
Asian-Australasian Journal of Animal Sciences, 2017
Ahead of Print article withdrawn by publisher.