Network analysis and optimization of animal transports

Sammanfattning: This thesis is about animal transports and their effect on animal welfare. Transports are needed in today’s system of livestock farming. Long transports are stressful for animals and infectious diseases can spread via animal transports. With optimization methods transport times can be minimized, but there is a trade-off between short distances for the animals and short distances for the trucks. The risk of disease spread in the transport system and disease occurrence at farms can be studied with models and network analysis.The animal transport data and the quality of the data in the Swedish national database of cattle and pig transports are investigated in the thesis. The data is analyzed regarding number of transports, number of farms, seasonality, geographical properties, transport distances, network measures of individual farms and network measures of the system. The data can be used as input parameters in epidemic models.Cattle purchase reports are double reported and we found that there are incorrect and missing reports in the database. The quality is improving over the years i.e. 5% of cattle purchase reports were not correctly double reported in 2006, 3% in 2007 and 1% in 2008. In the reports of births and deaths of cattle we detected date preferences; more cattle births and deaths are reported on the 1st, 10th and 20th each month. This is because when we humans don’t remember the exact number we tend to pick nice numbers (like 1, 10 and 20). This implies that the correct date is not always reported.Network analysis and network measures are suggested as tools to estimate risk for disease spread in transport systems and risk of disease introduction to individual holdings. Network generation algorithms can be used together with epidemic models to test the ability of network measures to predict disease risks. I have developed, and improved, a network generation algorithm that generates a large variety of structures.In my thesis I also suggest a method, the good choice heuristic, for generating non-optimal routes. Today coordination of animal transports is neither optimal nor random. In epidemic simulations we need to model routes as close to the actual driven routes as possible and the good choice heuristic can model that. The heuristic is tuned by two parameters and creates coordination of routes from completely random to almost as good as the Clarke and Wright heuristic. I also used the method to make the rough estimate that transport distances for cattle can be reduced by 2-24% with route-coordination optimization of transports-to-slaughter.Different optimization methods can be used to minimize the transport times for animal-transports in Sweden. For transports-to-slaughter the strategic planning of “which animals to send where” is the first step to optimize. I investigated data from 2008 and found that with strategic planning, given the slaughterhouse capacity, transport distances can be decreased by about 25% for pigs and 40% for cattle. The slaughterhouse capacity and placement are limiting the possibility to minimize transport times for the animals. The transport distances could be decreased by 60% if all animals were sent to the closest slaughterhouse 2008. Small-scale and mobile slaughterhouses have small effect on total transport work (total transport distance for all the animals) but are important for the transport distances of the animals that travel the longest.