This paper presents an application of the simulation of discrete events (SED) using ARENATM in the management of large-scale breeding farms. The main objective of the simulation model is to find a policy of replacemen...This paper presents an application of the simulation of discrete events (SED) using ARENATM in the management of large-scale breeding farms. The main objective of the simulation model is to find a policy of replacement, to ensure the best economic performance of a farm. The only variant analyzed of replacement policy was the number of cycles set in permanency for a sow in the herd. Considered incomes come from the sale of piglets and unproductive sows, and costs are due to the feeding of animals, replacement sows purchases, and the operation expenses of the farm. For this analysis, the production process was divided into three major stages called: mating, pregnancy or gestation and lactation. The sow’s movement from one stage to other was modeled by cycle-dependent transition probabilities. Considering the daily utility, as response variable, the model shows the best number of cycles to maintain the sows.展开更多
The replacement problem can be modeled as a finite, irreducible, homogeneous Markov Chain. In our proposal the problem was modeled using a Markov decision process and then, the instance was optimized using dynamic pro...The replacement problem can be modeled as a finite, irreducible, homogeneous Markov Chain. In our proposal the problem was modeled using a Markov decision process and then, the instance was optimized using dynamic programming. We proposed a new functional that includes a reward functional, that can be more helpful in processing industries because it considerate instances like incomes, maintenance costs, fixed costs to replace equipment, purchase price and salvage values;and this functional can be solved with dynamic programming and used to make effective decisions. Two theorems are proved related with this new functional. A numerical example is presented in order to demonstrate the utility of this proposal.展开更多
基金Instituto Tecnologico y de Estudios Superiores de Monterrey(Scholarship)Universidad Autonoma del Estado de Hidalgo,Secretaria de Educacion Publica(Complement scholarship)University of Lleida(Scholarship).
文摘This paper presents an application of the simulation of discrete events (SED) using ARENATM in the management of large-scale breeding farms. The main objective of the simulation model is to find a policy of replacement, to ensure the best economic performance of a farm. The only variant analyzed of replacement policy was the number of cycles set in permanency for a sow in the herd. Considered incomes come from the sale of piglets and unproductive sows, and costs are due to the feeding of animals, replacement sows purchases, and the operation expenses of the farm. For this analysis, the production process was divided into three major stages called: mating, pregnancy or gestation and lactation. The sow’s movement from one stage to other was modeled by cycle-dependent transition probabilities. Considering the daily utility, as response variable, the model shows the best number of cycles to maintain the sows.
文摘The replacement problem can be modeled as a finite, irreducible, homogeneous Markov Chain. In our proposal the problem was modeled using a Markov decision process and then, the instance was optimized using dynamic programming. We proposed a new functional that includes a reward functional, that can be more helpful in processing industries because it considerate instances like incomes, maintenance costs, fixed costs to replace equipment, purchase price and salvage values;and this functional can be solved with dynamic programming and used to make effective decisions. Two theorems are proved related with this new functional. A numerical example is presented in order to demonstrate the utility of this proposal.
