RetrieverBreeder
- Project name: RetrieverBreeder
- Class: 4IT496 (WS 2015/2016)
- Author: Bc. Lucie Pokorná
- Model type: Discrete-event simulation
- Software used: SimProcess, trial version
Recommended work outline:
Problem definition - a description of the situation you solve (i.e. the task) Method - the discussion of possible solutions, the selection of method and tools for the solution, reasons for such choice (why the selected methods and tools are the best for the problem) Detailed description of the method, including parameters, ranges, schemes, model limitations, etc. The description must be detailed enough that anybody could replicate the experiment event without your model source codes. Results - list of results, their analysis, interpretation and evaluation. Conclusion - how the problem was solved Citations Model source code (xls, spm, nlogo, mdl, etc. file)
Contents
Problem definition
Simulation should answer the question how many female dogs is optimal to keep for satisfying the demand for golden retriever puppies.
Detailed problem definition
he goal of the simulation is to simulate the whole simplified process to find the optimal amount of female golden retriever dogs owned and/or kept regarding all given variables and facts. Goal is to only have the ideal number of breeding dogs capable to fulfill the given birth giving plan and indirectly let the owner of a kennel satisfy the demand.
Method
When first seeing the SIMPROCESS possibilities and observing the way to show the simulation running, an idea of pet breeding simulation almost immediately came to mind. Such a simulation compound of the generating (literally generating in this case) an entity - puppy delivery, delay - puppy growth and then disposing the entity - either finding a match with a corresponding demand (a waiting customer), offering and older puppy for lower price, or just keeping the particular one in a kennel - is exactly the discrete-event type of simulation that could be shown quite transparently, comprehensible yet clearly enough using this simulation tool.
While the simulation has been conducted, no significant restrictions were found using just a trial version of the program. Few not that necessary activities had to be cut and the rest of the simulation optimized to make sure that the limit for a number of activities is not depriving the simulation of possibly interesting results.
Model
The simulation consists of 4 processes:
- "Birth giving" - puppy generating
- "Growing Up" - delay activity
- "Staying" - the kennel owner decides to keep a puppy
- "Leaving" - ideally a customer picks up a puppy, non ideally puppy is left "unwanted" for a longer period of time and has to be later sold for a lowered price or given entirely
Just one of the processes - the "Leaving" process - contains most of the activities used starting from the probability based division of puppy gender, customer decision making situation and handling an occasional exception - the case when there is no demand for a particular puppy and not even the kennel owner desires to keep it.
The simulation is set to be run in numerous iterations (replications). The more breeding female dogs the kennel owns, the more birth giving occasions there are. For the purposes of this simulation there is no need to simulate breeding dogs in any way, the only thing that is important is the recurrences of such events such is birth givings. It has been decided that each replication will simulate just a one litter had by one female breeding dog. In average, female golden retriever female is capable to give birth once a year and a half when the dog's health and well being is considered a number one priority. Simulation is set to show just a one such cycle. The lasting of a whole simulation including several replications is set to be an exact year and a half. That means that the number of replications equals to number of female breeding dogs within 18 months and actual breeding dogs as en entity or a resource may now be omitted in the simulation.
The distribution function for the demand is set to be invariable in a several runs of a simulation set period of time for a slight simplification. From a personal experience, demand for pedigreed puppies from a particular kennel changes quite a lot, yet the average remains at a very similar level, no matter how many puppies were sold in the past. It is possible and recommendable to adjust the value higher (lower) in a consequent time period - when the time simulated in a simulation passes - when the average demand grows (decreases) based on the actual demand counts have been observed and noted. The actual values are dependent on set number of replication.
- When a number of replications is changed, demands has to be modified as well. The demand is set to be around 25 BI(25, 0.5) customers desiring a male puppy and 30 BI(30,0.5) customers desiring a female puppy per 18 months. In case of having 5 breeding dogs (5 litters per 18 months), demand has to be divided by 5 to distribute evenly for each litter.
The model is based on real data gathered in the stated sources.
Entities
- puppy born at the beginning of the simulation
- Dog that the kennel owner decides to keep (and in case of a female dog potentially transform into a breeding dog, but that is not part of this simulation)
- Puppy that turned out to be a male
- Puppy that turned out to be a female
- Such puppy was not chosen by any customer during customer visitations and has to be treated in a different manner to make sure that it will find its new home
Resources
- Every puppy costs 222 USD per average to take care and nourish in the kennel - Puppy that survives the birth giving automatically consumes this resource
- A grown puppy costs additional 85 USD per average to take care and nourish in the later stages of its life - Such puppy has to be taken care of while waiting in the kennel
Demand has been implemented as a resource being used within the visitations activity. Binomial distribution functions was used
Processes
Results